Arnaud Badets
email: arnaud.badets@univ-poitiers.fr

Lucette Toussaint

Yannick Blandin

Christel Bidet-Ildei

Interference effect of body shadow in action control

Keywords: Cast shadow, automatic imitation, hand action

Observing actions performed by other persons can subsequently influence our own motor behaviors. However, it is unknown whether the shadows cast by such actions can also have an impact on the observers' action. Here we show that the mere observation of a cast shadow can influence imitative behaviors. Specifically, participants were shown a hand picture and its associated cast shadow in a neutral position. In a "compatible trial", the hand and shadow that followed were turned in the same open or closed direction, while in an "incompatible trial" the hand and shadow were turned in different directions. We contrasted two experimental conditions:

1) "Hand-Shadow" in which participants observed a hand and its cast shadow (the hand covered the shadow), 2) "Hand-Hand" in which participants observed a hand and another black hand (the shadow covered the hand). The participants' task was to imitate (i.e., by closing or opening their own hands) the hand or the cast shadow action. For both conditions, results revealed interference (i.e., longer response latencies) for incompatible trials. This suggests for the first time that the mere observation of a cast shadow of a hand can influence imitative behaviors. However, time courses of the response latencies revealed that imitative effect in the Hand-Shadow condition was different than the imitative effect in the Hand-Hand condition. Therefore, we suggest considering the cast shadow of an action as an important feature during motor control for humans.

Shadow in action 3

Observing another person performing actions can influence our subsequent motor behaviors [START_REF] Bandura | Social foundations of thought and action: A social cognitive theory[END_REF][START_REF] Mattar | Motor learning by observing[END_REF][START_REF] Heyes | Automatic imitation[END_REF]. For example, Press and colleagues (2005) asked participants to open or close their right hands as soon as they perceived a closing or opening movement of a human or a robotic hand. The results revealed a stronger interference when participants observed a human hand. Specifically, the response latencies increased drastically when participants were required to produce an incongruent movement (e.g., closing hand movement while observing an opening action) rather than a congruent one. This finding reveals a tendency to automatically imitate the actions of others [START_REF] Badets | Creating number semantics through finger movement perception[END_REF][START_REF] Stürmer | Correspondence effects with manual gestures and postures: a study of imitation[END_REF]Heyes, 2011, for a review). Interestingly, scholars have discovered that, at a neurophysiological level, such imitative behaviors are governed by an "action observation network" (AON) that includes the premotor cortex, the primary motor cortex, and the inferior parietal lobule (see [START_REF] Press | Action observation and robotic agents: learning and anthropomorphism[END_REF] for a review of the AON). This AON is active when people observe and then imitate the actions of others, and this activation is specific to human actions [START_REF] Press | Robotic movement elicits automatic imitation[END_REF][START_REF] Press | Sensorimotor experience enhances automatic imitation of robotic action[END_REF][START_REF] Press | Action observation and robotic agents: learning and anthropomorphism[END_REF]. However, during the observation of real life actions, the cast shadows of these actions are sometimes present in the visual scenes. For instance, during a soccer game with a shiny sun, the different body shadows projected on the ground could be processed as important features to take into account for different strategic behaviors like the precise positions of players between them. Yet, it is unknown whether such information can indeed influence motor performance of observers. The general aim of the present study was to test whether the cast shadow of an action can interfere with the mechanism of automatic imitation.

Cast shadows of objects are projected on a remote surface and provide important information (e.g., dispositions of objects in space) for visual processing (see Mamassian, Kill & Kersten, 1998 for this definition). From this perspective, cast shadows of objects represent fundamental cues for interaction with the environment [START_REF] Galfano | Long-lasting capture of tactile attention by body shadows[END_REF]. For instance, Bonfiglioli, Pavani and Shadow in action 4 Castiello (2004, Experiment 2) have found that if a cast shadow is dissimilar from the natural cast shadow of an object, the movement trajectory for a reach-to-grasp action toward this object is affected. To the authors, such findings suggested that the cast shadow of an object is processed during the control of an action. Interestingly, it has recently been suggested that a cast shadow of a body could provide a crucial tool for recognizing a person. For instance, the shadow of a person perfectly depicts the shape of the body, and it has been shown that individual identification is improved when judgments are based on the shadow cast on the ground in daylight in comparison to the conventional method in which identification is based on the actual body area [START_REF] Iwashita | Person Identification using Shadow Analysis[END_REF]. [START_REF] Pavani | Binding personal and extrapersonal space through body shadows[END_REF] have also suggested that such a cast shadow of the body could be an additional cue for sensorimotor representation. Specifically, they suggested that body shadows are involved in the elaboration of the "body schema" (see also [START_REF] Galfano | Long-lasting capture of tactile attention by body shadows[END_REF], which is a core representation of the positions of the parts of the body in space [START_REF] Whiteley | Visual processing and the bodily self[END_REF]. Note that the body schema is an important system for movement commands that includes, at a neuronal level, the parietal and the premotor cortex [START_REF] Giummarra | Central mechanisms in phantom limb perception: the past, present and future[END_REF], which are both areas of the AON [START_REF] Press | Action observation and robotic agents: learning and anthropomorphism[END_REF].

The AON also includes the primary motor cortex, which has been found to be a key locus in the observation of cast shadows of movements [START_REF] Alaerts | Observing shadow motions: resonant activity within the observer's motor system[END_REF]. In this study, Alaerts and colleagues asked participants to observe a hand or the shadow of this hand depicting a rhythmically adducted-abducted movement of the index finger. During this movement observation, transcranial magnetic stimulation was applied over the primary motor cortex of the participants while motor-evoked potentials (MEPs) were recorded from their index finger muscle. The results revealed that the MEP amplitude increased for the observation of the shadow or the real finger movements. The authors suggested that the observer's motor system (i.e., the AON; [START_REF] Press | Action observation and robotic agents: learning and anthropomorphism[END_REF] is active during the observation of a shadow depicting a movement or Shadow in action 5 the observation of the real action. Therefore, the mere observation of a shadow can have a strong influence on the motor system of observers (see also [START_REF] Sartori | Shadows in the mirror[END_REF] for similar interpretation). However, based on these studies of shadow movement, it is unknown whether the mere observation of a cast shadow of another person can also have an influence on subsequent movements of observers. To the best of our knowledge, the single piece of evidence for this assumption comes from an animal study. Indeed, animals such as crayfish can use the movement of a shadow projected on the ground to execute anti-predator behaviors [START_REF] Liden | Behavioral and neural responses of juvenile crayfish to moving shadows[END_REF]. For instance, if a shadow moves towards the animal at high velocity, the crayfish will stop its movement, likely in an attempt to reduce its visibility. This finding suggests that observing a shadow linked to an action of another can have a strong influence on subsequent motor behaviors.

Consequently, based on the AON for humans, it could be hypothesized that if a hand movement and the shadow of this hand can influence the motor system [START_REF] Alaerts | Observing shadow motions: resonant activity within the observer's motor system[END_REF], we should find an automatic imitation effect from the hand, and also the cast shadow movement.

In the present study, participants were asked to observe two stimuli and to open or close their right hand in response to a change in only one stimulus. The stimuli were a hand and its cast shadow in a neutral position and the hand and its cast shadow turned into an opening or closing position (Figure 1, panel A). For the Hand-Shadow condition (HS), the cast shadow was projected on a remote surface and did not cover the hand [START_REF] Mamassian | The perception of cast shadows[END_REF]. With this stimulus configuration, we expected to provide participants with an adequate correspondence between the hand and its cast shadow. [START_REF] Mamassian | Impossible shadows and the shadow correspondence problem[END_REF] suggested the following for the cast shadow information: "in order to use that information, our visual system has first to segment regions in the image, decide that these regions are potential shadows rather than, say, ink blots, and then match these shadow candidates with objects in the scene. We call this last processing stage the "shadow correspondence problem"." (p.1279). For the Hand-Hand condition (HH), the shadow Shadow in action 6 covered the hand and, consequently, could not be interpreted as a cast shadow but, more likely, as another hand. Indeed, we reasoned that if the shadow was presented as covering the hand, the shadow correspondence would be impossible for the participants [START_REF] Casati | Some varieties of shadow illusions: Split shadows, occluded shadows, stolen shadows, and shadows of shadows[END_REF][START_REF] Mamassian | Impossible shadows and the shadow correspondence problem[END_REF]. Consequently, the participants should interpret this stimulus as a second hand because, despite its black color, a cast shadow cannot cover a hand under natural conditions. To ensure that our assumptions were correct, a post-experimental interview about these stimuli was recorded by the experimenter at the end of the study.

The participants were instructed to follow the action of one of two stimulus positions. For instance, in the first block of the HS condition, the participant was asked to follow the firstposition stimulus. Consequently, this participant's task was to open his/her hand when the hand stimulus (i.e., the first-position stimulus) turned in the open direction. Note that participants were instructed not to pay attention to the second-position stimulus (i.e., the cast shadow). However, this second-position stimulus could turn into a compatible or incompatible direction (opening or closing, respectively). For a second block of trials, the participants were instructed to follow the second-position stimulus (i.e., the cast shadow), and, consequently, the compatible and incompatible directions came from the hand action.

From the theoretical background developed in the present paper and our experimental paradigm, we expected to confirm four main hypotheses. First, we expected that participants would interpret (assessed through the post-experimental interview) the two stimuli differently, that is, a hand and its cast shadow in the HS condition and two hands in the HH condition. Indeed, as emphasized by the definition of a cast shadow [START_REF] Casati | Some varieties of shadow illusions: Split shadows, occluded shadows, stolen shadows, and shadows of shadows[END_REF][START_REF] Mamassian | The perception of cast shadows[END_REF], it is highly improbable that participants recognize as a shadow a stimulus that covers the hand. Second, for the HH condition we predicted a classical interference effect. Indeed, participants should interpret both stimuli as two hands, and as suggested by Press and colleagues (2005; see also [START_REF] Stürmer | Correspondence effects with manual gestures and postures: a study of imitation[END_REF]Heyes, 2001) the mere observation of a hand mimicking an action can induce a strong Shadow in action 7 automatic imitation even when the second stimulus is task-irrelevant (see also [START_REF] Brass | Movement observation affects movement execution in a simple response task[END_REF] for finger movements). Third, and most importantly, in the HS condition, we predicted an interference effect from the cast shadow action as hypothesized by Alearts et al. (2009). Indeed, based on the different findings regarding the cast shadow of the body [START_REF] Galfano | Long-lasting capture of tactile attention by body shadows[END_REF][START_REF] Iwashita | Person Identification using Shadow Analysis[END_REF]Pavani & Castiello, 2004;[START_REF] Pavani | Self-attributed body-shadows modulate tactile attention[END_REF], we expected that the mere observation of a cast shadow of a hand action could have a strong influence on the motor system of the observers. Specifically, our data should reveal an interference effect in the imitative behavior in the condition in which the participants followed the hand regardless of whether they were asked to ignore the cast shadow. Finally, if the participants interpreted a hand with its cast shadow for the HS condition, the two stimuli could represent a single action from a single hand (a correct shadow correspondence). Conversely, if the participants interpreted two hands from the HH condition, then the two stimuli could represent two different actions. Consequently, based on the biological specificity of the AON, we predicted that the two biological hands of the HH condition could interfere more strongly than a single hand with its cast shadow could. To test this last hypothesis, we have used an analysis on the distribution from the fastest to the slowest responses times (see [START_REF] Catmur | Time course analyses confirm independence of imitative and spatial compatibility[END_REF][START_REF] Brass | Movement observation affects movement execution in a simple response task[END_REF] Experiment 2; [START_REF] Press | Robotic movement elicits automatic imitation[END_REF] for similar analysis in imitation paradigms). In this perspective, Brass and colleagues found that the compatibility effect during an imitation task of a biological stimulus was larger for slower responses (see also [START_REF] Press | Robotic movement elicits automatic imitation[END_REF]. This finding is interpreted as the imitation processes underlying compatibility effect becomes more implicated over time.

Consequently, we could expect the same effect when the biological specificity of the AON is fully engaged, that is, in the HH condition.

Method

Participants. Thirty-six (34 right-handed and 2 left-handed) French-speaking students from the University of Poitiers (mean age: 19.8  1 year; 25 males) participated in this study for course Shadow in action 8 credit and were distributed equally in each group through hand-laterality. All participants had normal or corrected-to-normal vision, were unaware of the experimental goals, and provided informed and signed consent. The experiment was non-invasive and was performed in accordance with the ethical standards established by the Declaration of Helsinki.

Stimuli, apparatus and task. The stimuli were right male hands presented in their natural colors.

The neutral and opening position involved a distance of 3.5 and 9.5 cm, respectively, between the index finger and thumb. In the closing position, the thumb was shown joined with all other fingers. Length (L) and Height (H) of the neutral, opening and closing positions occupied a window of 5 cm x 10 cm, 10.5 cm x 8.5 cm and 5cm x 9 cm respectively which corresponded to the actual visual angles 4.8° (L) x 9.7° (H), 10.02° (H) x 8.1° (L), and 4.8° (H) x 8.6° (L) at a viewing distance of 60 cm. The cast shadow was the same hand figure presented in grey color mimicking a real shadow (Figure 1, panel A). The apparatus consisted of a PC computer equipped with a 43.17 cm (diagonal) screen and a manual-response device composed of two microswitches (see Figure 1, panel B). The microswitches were connected to the PC computer, and a customized E-Prime® program controlled the experimental procedure and stored the raw data for offline analysis. Using the manual-response device, the participant's task was to open or close his or her right hand when an opening or closing hand or cast shadow appeared on the screen. Figure 1, panel B, shows the participant's task. For the neutral position (middle picture), microswitches A (bottom small strip) and B (the top small strip) are in the "on" and "off" positions, respectively. For the opening position (top picture), microswitch A is released and turns into the "off" position. For the closing position (bottom picture), microswitch B is squeezed and turns into the "on" position. Note that from the neutral position, the PC computer stored a valid manual response with its respective response latency from the "off" and "on" position of the microswitches for the opening and closing movements of the participant, respectively. the other half the shadow stimuli were presented slightly over the hand stimuli (see Figure 1A).

Shadow in action 9

Both the stimulus presentations and the compatible and incompatible trials were presented randomly during the experiment.

In total, 2 blocks of 120 trials were presented to the participants. For the first and second blocks, the participants were required to follow the first-position and the second-position stimulus, respectively. This rule was counterbalanced across participants. For each block, 60 compatible trials and 60 incompatible trials were presented. At the end of the experiment, participants answered the following question: "what did the stimuli on the screen represent?" This question was given in French (i.e., "que représentaient les stimuli à l'écran de l'ordinateur?").

Shadow in action 11 Participants were instructed to respond as simply as possible, and the experimenter noted these responses on a sheet of paper.

Design. The independent variables included CONDITIONS (Hand-Hand vs. Hand-Shadow) as a between-groups factor, and RULES (first-position vs. second-position) and COMPATIBILITY (compatible vs. incompatible) as within-group factors.

Dependent variables. We used the mean response latency (in ms) as dependent variables [START_REF] Press | Robotic movement elicits automatic imitation[END_REF][START_REF] Press | Sensorimotor experience enhances automatic imitation of robotic action[END_REF]. The response latency was calculated from the presentation on the screen of the apparent closing or opening action of the hand or the shadow to the opening or closing movement of the participant. In our analyses, we excluded trials with errors related to the COMPATIBILITY (averaging 2.3%). Response latencies were then submitted to an analysis of variance (ANOVA), and post-hoc comparisons were computed using Duncan's technique. All significant effects were reported at p < 0.05 (unless otherwise noted).

For the question asked at the end of the experiment, a chi-square test was conducted to assess whether different types of responses were chosen in the two different conditions (the HS and the HH condition). Specifically, we attributed a numeric value of "1" for each response that included one of the following statements: "I have seen two hands" or "I have seen a hand and its shadow" or "I have seen a hand and an object". Note that the first and second answers correspond to the HH and HS condition, respectively. It is worth noting that the last response was never given by participants.

Results

Stimulus representation. For the question ("what did the stimuli on the screen represent?"), sixteen participants in the HH condition reported that the stimuli presented on the screen were two hands, that is, one in a black color and another in a real color. Two participants reported that the stimuli were a hand and a shadow because a shadow is generally black in color. For the HS Shadow in action 12 condition, fifteen participants reported that the stimuli were a real hand with its cast shadow, but three participants reported two different hands because the two stimuli did not move in the same direction. A chi-square test indicated a significant difference in responses between the HH and the HS conditions (  [1] = 18.8; p < .0001). This analysis revealed that participants more frequently interpreted the HH condition as two hands (88.9%) and the HS condition as a hand and its cast shadow (83.3%).

Response latency. The dependent variable was analyzed in a 2 CONDITIONS (Hand-Hand vs.

Hand-Shadow) X 2 RULES (first-position vs. second-position) X 2 COMPATIBILITY (compatible vs. incompatible) ANOVA with the last two factors defined as within-group independent variables. The analysis revealed a main effect only for COMPATIBILITY (F[1, 34] = 106.2, p < .00001, η² p = .75). This effect indicated that for both conditions, the participants responded faster for compatible than for incompatible trials (see Figure 2

Shadow in action 13

To explore whether the compatibility effect had different temporal dynamics for the HH and HS condition, a distribution analysis was performed on response latencies [START_REF] Ratcliff | Group reaction time distributions and an analysis of distribution statistics[END_REF].

For this purpose, we divided the response distribution of each participant into ten "bins" ranging from the fastest to the slowest response times. The dependent variable was then analyzed in a 2 CONDITIONS (Hand-Hand vs. Hand-Shadow) X 2 COMPATIBILITY (compatible vs. incompatible) X 10 BINS ANOVA with the last two factors defined as within-group independent variables. The analysis revealed a main effect for COMPATIBILITY (F[1, 34] = 95.4, p < .00001, η² p = .73), BINS (F[9, 306] = 409.3, p < .00001, η² p = .92), a significant CONDITIONS X BINS interaction (F[9, 306] = 1.9, p < .04, η² p = .05), and a significant COMPATIBILITY X BINS interaction (F[9, 306] = 2.6, p < .005, η² p = .07). Most importantly, the analysis revealed a significant CONDITIONS X COMPATIBILITY X BINS interaction (F[9, 306] = 3.02, p < .001, η² p = .08). For this last interaction (see Figure 3), post-hoc analysis revealed that for the bins 1, 2, and 3, there is no compatibility effect for both conditions. The compatibility effect appeared for both conditions and grew up from bins 4 to 9. However, for the last bin, there is a significant compatibility effect only for the HH condition. In other words, for both conditions there is an identical compatibility effect for bins 4-9, but this effect vanished to the slowest response time for the HS condition.

Shadow in action 14

Discussion

The general aim of this study was to assess whether the mere observation of a cast shadow of a hand action could influence the observers' own hand movement. In the HS condition, participants were required to observe a hand that performed a movement of opening or closing its fingers. In some trials, the cast shadow of this hand followed the hand (compatible trials), and in other trials, the hand and cast shadow moved in the opposite way (incompatible trials). The response times clearly indicate that the mere presentation of a cast shadow can influence the observers' capacity to follow the moving hand. Specifically, response times were longer for incompatible than for compatible trials. The distribution analysis revealed that this effect was present for the HS condition only for the bins 4-9. For the HH condition, the effect was also present for the slowest responses (i.e., the last bin). Altogether, these findings confirmed the strong effect of biological stimuli during an imitation task [START_REF] Brass | Movement observation affects movement execution in a simple response task[END_REF][START_REF] Press | Robotic movement elicits automatic imitation[END_REF]), but more importantly, that a body shadow associated with its action can be interpreted as an important feature for the action control of observers.

Shadow in action 15

The present study confirmed that for the HH condition and for the HS condition, the participant perceived two hands or a hand and its cast shadow, respectively (see the stimulus representation section). This result suggests that when a hand covered the shadow that is, a shadow projected on a remote surface, the participants interpreted this stimulus as a cast shadow [START_REF] Mamassian | The perception of cast shadows[END_REF], see Casati, 2012;[START_REF] Mamassian | Impossible shadows and the shadow correspondence problem[END_REF] for this shadow correspondence effect). In contrast, when the shadow covered the hand, this stimulus was interpreted as another hand. Moreover, the factor RULES (first-position vs. second-position) did not interact with other factors (Fs < 1). This result indicates that in the HS condition, the shadow influenced the observer's action to the same extent than the hand stimulus, at least for the bins 4-9. In other words, there was no more interference from the shadow or the hand stimulus. Consequently, we assume that for the HS condition, participants perceived a single hand. Our interpretation is that, if this single hand displayed incongruent information (from the hand itself or its cast shadow) depending of the action to-be-performed, an inference occurred in the AON of the observers.

To summarize the present findings, we confirmed the main hypotheses presented in the introduction section. First, through the configuration of the stimuli [START_REF] Casati | Some varieties of shadow illusions: Split shadows, occluded shadows, stolen shadows, and shadows of shadows[END_REF][START_REF] Mamassian | Impossible shadows and the shadow correspondence problem[END_REF], the participants interpreted the HH and HS conditions as two hands or as a hand and its cast shadow, respectively. Second, the configuration of two hands (i.e., HH), or a hand with its cast shadow afforded interference as suggested by the AON [START_REF] Alaerts | Observing shadow motions: resonant activity within the observer's motor system[END_REF][START_REF] Press | Action observation and robotic agents: learning and anthropomorphism[END_REF].

Thus, the observation of cast shadow of an action can influence the motor control of observers.

However, the distribution analysis of response times revealed that the interference was always present for the slowest response latencies only for the HH condition. Consequently, the hand and its cast shadow seem weaker to create the same level of interference in the motor system of the observers than the HH condition. Based on the biological specificity of the AON [START_REF] Press | Action observation and robotic agents: learning and anthropomorphism[END_REF], this last finding accord with the assumption that the interference should be stronger from two hands than a single one.

Shadow in action 16

It is worth noting that our results are in accordance with the finding that in an automatic imitation paradigm, incompatible trials induce stronger interference than compatible trials do [START_REF] Heyes | Automatic imitation[END_REF][START_REF] Press | Robotic movement elicits automatic imitation[END_REF][START_REF] Press | Sensorimotor experience enhances automatic imitation of robotic action[END_REF][START_REF] Stürmer | Correspondence effects with manual gestures and postures: a study of imitation[END_REF]. We found this interference effect in the HH and the HS condition for the bins 4-9 which represented a speed distribution for response times from 350 to 500 ms. For comparable speeds of response times, other studies have found the same interference effect for different imitation paradigms (Brass et al. 2001, Experiment 2;Catmur & Heyes, 2001;[START_REF] Press | Robotic movement elicits automatic imitation[END_REF]. Our present design is also comparable to the study by [START_REF] Stürmer | Correspondence effects with manual gestures and postures: a study of imitation[END_REF] in which participants had to grasp or to spread their hand apart after the perception of a color change in the model's hand. In this study, the color change is the imperative stimulus, and the model's hand can be congruent (compatible trials) or incongruent (incompatible trials) depending on the action to be performed. Though our study utilized a different stimulus (a hand position), we also found longer response latencies in incompatible trials than in compatible trials.

This finding for the HH condition suggests that we have perfectly replicated the classical effect of the automatic imitation domain, that is, the human tendency to copy the actions of others [START_REF] Heyes | Automatic imitation[END_REF][START_REF] Press | Action observation and robotic agents: learning and anthropomorphism[END_REF].

However, using the same design for the HS condition, the interference effect (reflected by the distribution analysis) was less because the slowest response times (the last bin) were the same for both compatible and incompatible trials. To interpret this, we suggested above that when participants perceive a cast shadow with a single hand, the AON is less active than the perception of two hands (i.e., the HH condition). Another interpretation could be that perceiving a hand and its cast shadow as we presented them in the incompatible trials (e.g., the hand closing and the shadow opening) can be highly irrelevant for the observers because this situation is impossible in a real life situation. For participants in the HS condition, this improbable situation may have afforded no significant interference, which, in turn, did not influence to the capacity to copy the model's action, especially during longer response times (around 700 ms). In other words, Shadow in action 17 participants took advantage of their longer response times in order to reject or to inhibit such improbable information from the AON. In agreement with this assumption of different levels of interference, Costantini and colleagues (2005) have found specific activation in sensorimotor parietal areas during the observation of biomechanically impossible movements of fingers. However, our current findings should be interpreted with caution and require further empirical evidences to fully confirm our assumptions about the role of a body shadow in motor control. Indeed, as suggested by an anonymous reviewer, our general interpretation about the distinction between the HH and the HS condition is only based on the last bin of the distribution analysis and a post-experimental interview about the stimuli. Specifically, it is difficult to rule out entirely the possibility that during the experimental task, the participants did not process areal hand for the black stimulus in the HS condition, especially for bins 1-9 which showed exactly the same pattern of results for both HH and HS conditions. Accordingly, the present study gives a weak but preliminary support for the general claim about the specific role of cast shadows in the imitative behaviour of observer. So far, more studies are needed in order to fully confirm whether the AON is less active because participants process one single hand with its associated shadow for the HS condition in comparison to two hands for the HH condition.

Finally, as suggested by [START_REF] Pavani | Binding personal and extrapersonal space through body shadows[END_REF] see also [START_REF] Galfano | Long-lasting capture of tactile attention by body shadows[END_REF], the main role of a body shadow is most likely to afford additional information for the sensorimotor representation and, specifically, the body schema. For these authors, the cast shadow of a body can be crucial in isolating the self from the environment and, especially, in constructing the gap between personal and extrapersonal space (Pavani & Castiello, 2004). This suggestion is in accordance with the view that the AON is also involved in distinguishing the self from the other and, more precisely, in understanding the actions of others [START_REF] Neal | What is simulated in the action observation network when we observe actions[END_REF]Rizzolatti & Sinigaglia, 2010, for a review). From an evolutionary perspective, [START_REF] Pavani | Self-attributed body-shadows modulate tactile attention[END_REF] suggested the following regarding body shadows: "They have presumably accompanied humans Shadow in action 18 throughout evolution providing important cues for self-recognition, as well as recognition of bodies of other approaching living creatures." (p. 86). Similarly, [START_REF] Rizzolatti | The functional role of the parieto-frontal mirror circuit: interpretations and misinterpretations[END_REF] suggested of the AON that "Such motor-based understanding seems to be a primary way in which individuals relate to one another, as shown by its presence not only in humans and monkeys, but also in evolutionarily distant species, such as swamp sparrows and zebra finches." (p. 273).

Consequently, based on the present automatic imitation paradigm, which has been used to test the AON [START_REF] Heyes | Automatic imitation[END_REF][START_REF] Press | Action observation and robotic agents: learning and anthropomorphism[END_REF], we suggest that the interference effect found for the HS condition is the first behavioral evidence of this cast shadow account system for action control in human observers (see [START_REF] Liden | Behavioral and neural responses of juvenile crayfish to moving shadows[END_REF], for a behavioral interpretation in crayfish). In line with this evolutionary perspective, it has recently been suggested that parts of the AON could be involved in understanding the actions of others to develop defensive behaviors for observers of different species [START_REF] Blanchard | Risk assessment as an evolved threat detection and analysis process[END_REF]. Defensive behaviors could also develop in humans through cast shadow processing inside the AON.

Conclusion

Body shadow can have a specific influence on action control. The observation of such a shadow can involve the primary motor cortex of observers [START_REF] Alaerts | Observing shadow motions: resonant activity within the observer's motor system[END_REF]) and, at a behavioral level, can present important information for the formation of sensorimotor representation (Pavani & Castiello, 2004). The present study follows this line of research and demonstrates for the first time that shadow is also functionally implicated in the motor system of observers during imitation. Theoretically, this implication suggests that the body shadow is likely an important feature for the AON system. However, additional empirical studies at a behavioral and neurophysiological level are needed to fully encompass our preliminary findings about the precise role of shadow in actions.

  Figure 1. (A) Neutral, compatible and incompatible stimuli representing the hand and its cast shadow for the HS and HH conditions. (B) Manual-response device in the opening, neutral and closing position; A and B represent the microswitches, the white arrows represent the directions of the opening and closing action from the neutral position, and the black arrows represent these actions from the neutral to the opening and closing positions. (C) Temporal sequence of events for a trial in the HS condition. For each trial, neutral stimuli were displayed and changed into compatible or incompatible stimuli. The same sequence was used for the HH condition.

  ). No main effects from CONDITIONS (F[1, 34] < 1) or RULES (F[1, 34] = 1.8, p = .18) and no interaction between CONDITIONS and COMPATIBILITY (F[1, 34] = 1.2, p = .27), or other factors (Fs[1, 22] < 1) were observed.

Figure 2 .

 2 Figure 2. The mean response latencies for the Hand-Hand condition and the Hand-Shadow condition as a function of compatibility. * indicates significant differences and error bars represent 1 Standard error.

Figure 3 .

 3 Figure 3. Mean response latencies in each bin as a function of compatibility for the Hand-Hand and Hand-Shadow condition. * indicates significant differences, and error bars represent 1 standard error.

Acknowledgments

We are grateful to Cédric Bouquet and Yves Almecija (CNRS-UMR-7295) for their valuable comments regarding the editing of the pictures and the device used in the present study.

Shadow in action 20


Nicolas Gonzalez
email: ngonzalez@snootlab.com

Adrien Van Den Bossche

Thierry Val
email: val@irit.fr

Specificities of the LoRa™ Physical Layer for the Development of New Ad Hoc MAC Layers

The Internet of Things and particularly energy constraint object revealed these last years some radio frequencies technologies which allow to realize wireless transmissions at long range and with low energy. This change of paradigm makes tip over the problems of multi-hop networks to multi-channel MAC networks. The LoRa™ technology arises from this sphere of influence by using the spread spectrum to reach the expected performances. This physical layer is very original compared with the physical layers used for a long time with the IEEE 802.15.4 standard. This article highlights the specificities of the LoRa™ physical layer to design new MAC layers for the ad hoc Internet of Things.

Introduction

The Internet of Things (IoT) is a growing field. This is a relatively large area of application where many scientific, technological and societal issues arise. Technologically, IoT can be addressed by the data side or by the network side. Regarding the network part, we distinguish the collection network, wireless and energy constrained, from the rest of the backbone constraints and challenges are not the same. It is considered that the wireless part of the IoT (Device-Layer of the IoT [START_REF] Khan | Future internet: the Internet of Things architecture, possible applications and key challenges[END_REF]) inherits ad hoc mobile networks (MANET) and wireless sensor networks (WSN) from the proximity of constraints and latches [START_REF] Bellavista | Convergence of MANET and WSN in IoT urban scenarios[END_REF]. However, recent technological advances in narrow-band (NB) and ultra-narrow-band (UNB) technologies are opening up new possibilities, such as radio range, topologies, and multi-channel access. These possibilities make it possible to consider new collection network, especially at the MAC level. This is for example the case with LoRa™ technology, the acronym for "Long Range" which is a NB wireless transmission technology for long range and energy efficient transmissions for the node sensors. Thanks to its various parameters, LoRa™ makes it possible to imagine new medium access controls. This article proposes to list the different technical levers that the LoRa™ radio physical layer offers and to study the performances outside any MAC consideration. This study shows the beginnings of the development of new MAC layers for the Internet of Things.

This article is structured as follows: after this introduction, we present in more detail the problematic of the transition from multi-hop to multi-channel. Next, we present a detailed analysis of the LoRa™ technology and the different levers that it allows to activate, particularly in terms of the isolation of logical channels, followed by a state of the art of the techniques for using these methods. Then we present an experimental study evaluating, on a real test bench, the logical isolation capacity offered by LoRa™. In a final part, we present ways to improve MAC mechanisms in LoRa™, before concluding the article.

2 Problem: From Multi-hop to Multi-channel For many years, in the dynamics of the IEEE 802.15.4 standard, a major difficulty in scaling up the number of nodes is at the routing level. The very limited resources in terms of datarate, computational performances and energy of the nodes of this type of network do not make it possible to search and find routes efficiently on a large number of nodes of the global network. The IEEE 802.15.4 standard, heavily used in recent years, mainly uses physical layers that have a fairly high throughput for a sensor network (250 kbit/s) but whose range is limited (200 to 300 m in outdoor and 30 m in indoor ).

The use of physical layers like LoRa™ makes it possible to greatly increase the radio range, which has the effect of changing the type of topology, protocol architecture and therefore globally, paradigm [START_REF] Pham | QoS for long-range wireless sensors under duty-cycle regulations with shared activity time usage[END_REF]. It is interesting to note that for the usual applications of the Internet of Things, with an equal node density, for a LoRa™ network, the density of the links increases and the distance in number of jumps decreases, compared to a network 802.15.4. The Fig. 1 makes it possible to represent this change of scale at the level of the radiofrequency cells. This last point makes it possible to release the constraints on the layer 3 and on the multi-hops routing algorithms. However, this constraint is transferred to the MAC layer because with the increasing density, a larger number of nodes must share the medium on the same local geographical area. This disadvantage is accentuated by a longer transmission time, which collapses the capacity of the medium.

Fig. 1. From multi-hop to multi-channel

It is necessary, at the MAC level, to take advantage of the possibility of instantiating several channels in order to distribute the nodes on all the available channels and to find suitable temporal performances, thus making it possible to scale up.

Analysis of the Levers Offered by LoRa™

LoRa™ is a narrow-band wireless transmission technology, which gives it a high degree of robustness (high receiver sensitivity, long range). The trade-off that needs to be made is at fairly low throughput. There is also a limitation of the emission duty cycle (duty cycle) related to the fact that the LoRa™ modulation is intended for ISM bands (Industry, Scientific and Medical) which are unlicensed bands. These bands are said to be unlicensed because they can be used by any user without a license, which favors the uncoordinated deployment of varied and generally incompatible networks. This is an essential detail in our reflection because the use of these bands can be very strong and they can be very polluted and electromagnetically congested.

LoRa™ technology is based on CSS (Chirp Spread Spectrum) which is a particular spread spectrum technique. The goal of the CSS techniques is to spread the spectrum on different frequencies and on different instant of the time by adding both a strong redundancy and a correlation in the signal in order to greatly increase the robustness thus limiting the multipath phenomena. This modulation is obtained by coding the information using orthogonal codes, quantified by the Spreading Factor (SF). In the next section, the different parameters of the LoRa™ physical layer are presented.

LoRa™ Physical Layer Settings

Spreading Factor. In order to increase the reliability of the transmission and thus make it possible to send messages at long range, the LoRa™ modulation uses a strong redundancy of information. For this, each bit of the message is coded by a symbol composed of several bits. In this way, it is much more difficult to confuse a '1' or a '0' received. This increases the signal-to-noise ratio, which makes it possible to reach objects in harsh environments or at longer distances. The SF simply corresponds to the number of "bits" per symbol. The Table 1 shows the different spreading factors currently available in LoRa™ tranceivers. A Chirp is a frequency sweep used by CSS to represent a bit at the physical level. The number of Chirp/symbol represents the number of symbols at the physical level to represent a bit of information. This metric gives us the number of symbols used to represent a bit of information, so this is the coding efficiency at the physical level. For each SF, there are two codes, one for the '0' symbol and one for the '1' symbol. Note that the more the SF increases, the longer the code length is and therefore the lower the useful bit rate is. When we increase the SF by 1, we multiply the length of the code by 2 and thus we divide the data rate by 2. According to the Friis formula (1), one can deduce that a gain of 6 dB on the link budget makes it possible to double the transmission range. For example, moving from a SF 7 to a SF 12, improves the coding gain of +12.5 dB. This gain makes it possible to have a transmission distance multiplied by four. The Friis model is a simple model that is not adapted to a Smart City environment but we use it here to just give an idea of the impact of the spreading factor.

P r = P t + Gt + Gr -32.45 -20 × log(f req) -20 × log(rang) (1)
Pt : Emission power Pr : Reception power Gt : Gain of the reception antenna Gr : Gain of the emitter antenna freq : Emission frequency in MHz rang : Range in km An important property of the SF is that the codes used are orthogonal to each other from a mathematical point of view. That is, from a theoretical point of view, a message coded with a certain SF can not influence a message with another SF present at the same time on the same medium, in the same place. We are in the presence of several logical channels, even if they are on the same frequencies. Of course, the LoRa™ modulation requires that the receiver and the transmitter are parameterized with the same SF to be able to communicate together. It is very interesting to note that in the current LoRa™ radios, there is a technological difference between an end-device and a gateway. A gateway is able to receive messages with different Spreading Factors without having to reconfigure its radio. This property allows it to have a privileged place in the network, however, it is still bound to the same legislation as the End-Devices.

Coding Rate. The LoRa™ modulation natively uses cyclic redundancy codes, of the Hamming code type, which make it possible to check the integrity of the message received. This check is performed after receiving a message to the correct SF. The tranceiver automatically recalculates the cyclic code and depending on the result decides whether or not to validate the received message. In the header of the physical layer, there is a field that indicates the coding rate of the message. This allows a receiver to receive messages with different coding rates. On the other hand, the coding rate does not make it possible to create new channels unlike the SF! The array Table 2 shows the different possible coding rate values in a LoRa™ tranceiver. Bandwidth. Bandwidth (BW) is the bandwidth used during a transmission. It is expressed in Hertz. For the modulation LoRa™, it is possible to send a chirp per second and per Hertz of bandwidth. That is, if you select a bandwidth of 500 kHz, you will be able to send 500000 chirps per second. Depending on the SF and the Coding Rate that we have chosen, we will be able to determine the maximum possible data rate. According to [START_REF] Augustin | A study of LoRa™: long range & low power networks for the Internet of Things[END_REF], the division of the value of BW by two makes it possible to gain 3 dB of additional sensitivity. According to the formula Friis (1), a 125 kHz emission instead of 500 kHz allows to gain 6 dB and thus to double the transmission range in free field.

LoRa™ Logical Channels

In our problem of densification of nodes in radio range, it is necessary to make the best use of the available parameters in order to create a multitude of subsets of communication channels that do not interfere with each other. Here in after, we briefly present the frequency and time division techniques that have already been used. In a second step, we will present the creation of channels by coding using the SF.

Channels by Frequency Division. It is currently possible to use LoRa™ directly in the 433 MHz, 868 MHz and 2.4 GHz bands due to the availability of associated transceivers on the market. For example, the SX1276, the SX1272 and the RN2483A. Take for example the 868 MHz band in Europe that is used by the LoRaWAN protocol. LoRaWAN is a MAC and network protocol based on a LoRa™ physical layer. This band ranges from 868.0 MHz to 868.6 MHz with a radiated power limit of +14 dBm, a duty cycle of less than 1% and no limit on bandwidth [START_REF]ERC Recommendation 70-03, Relating to the use of Short Range Devices (SRD)[END_REF]. Therefore, it is possible to divide this 600 kHz band into several frequency channels. This is what was decided for the LoRaWAN protocol with the use of three main channels at 868.10 MHz, 868.30 MHz and 868.50 MHz center frequencies. On these bands, it was chosen to use a bandwidth of 125 kHz, which leaves a width of 75 kHz between the channels. We see that it is possible to go much further in the cutting of this band, using channels with different bandwidths for example.

Channels by Time Division. As with other radio technologies, it is possible to set up a time multiplexing of transmissions. The specificity, however, is that currently, LoRa™ is used on the so-called 'ISM' bands and that the limitation of these unlicensed bands obliges an emitter to respect the duty cycle limitation at 1% maximum. This imposes a cumulative total issue time of 36 s maximum over a rolling hour. The limitation on the transmission time is 3.6 s and 1.8 s between two transmissions. With a relatively standard setting (SF7, 125 kbps) a frame of 30 bytes lasts 70 ms on the medium. With the legal limitation, it is possible to send 514 messages per hour. This limitation on the duty cycle is not applicable if the MAC layer implements a Listen Before Talk (LBT) mechanism, i.e. an analysis of the free or busy medium before sending. The effect of LBT is similar to that of Clear Channel Assessment (CCA) used in CSMA/CA type MAC protocols but not based on an energy threshold.

Channels by Coding.

Coding multiplexing is the most original and interesting for the LoRa™ physical layer. Indeed, the use of SF will allow to create a third dimension of channels. As the codes used by the different Spreading Factors are orthogonal, it is possible to perform simultaneous transmissions on the same medium air while avoiding collisions. It is conceivable to think that, as there are 7 spreading factors (from 6 to 12), the number of channels available by time and/or frequency multiplexing is multiplied by 7. It should be noted that the SF 6 is a bit special because it requires the use of the implicit mode which is a payload transmission mode of fixed size. However the choice of a SF is not insignificant! The first remark is the emission time that evolves at power 2 according to the SF. At the same time, the robustness of the signal is improving! We will therefore be able in a given frequency channel to create several channels depending on the state of the link. A transmitter that is very far from the receiver or in adverse conditions will be able to change SF to pass on a more robust channel, and better radio range.

Synthesis. The use of LoRa™, in unlicensed bands today, allows via different techniques to make many logical channels. It must be remembered that despite all the use of unlicensed bands imposes a limitation of the duty cycle which is in no way solved by multi-channel MAC techniques. The coding channels are very original and interesting in the LoRa™ technology because they allow very different channels in terms of range and robustness. This diversity of channel parameters could be used to setup the physical layer according to the range between two nodes. An important parameter for MAC layer development is the impact of synchronization on performance. Indeed, the logical tightness between the channels must not be dependent on the temporal phase shifts between the channels because it is a very difficult problem to solve.

Related Works

The most deployed MAC layer based on a LoRa™ physical layer is LoRaWAN. This MAC layer already uses datarate adaptation mechanisms, by changing SF and transmission power, in order to optimize communications [START_REF][END_REF]. It is the device (connected sensor) and not the central base station, which can choose to automatically adapt its parameters or ask the network to determine them. LoRaWAN therefore already uses a SF pluralism mechanism but only for the purpose of optimizing static devices. This is not enough because the goal for LoRaWAN is to optimize the objects independently and not to distribute them intelligently in channels.

The joint optimization strategy of the transmission power and SF is justified by [START_REF] Ochoa | Evaluating LoRa energy efficiency for adaptive networks: from star to mesh topologies[END_REF] because changing SF is much less optimal from an energy point of view than increasing the transmission power. The strategy to optimize the robustness of the links is to increase the transmission power to a point where it is more optimal to change the SF and reduce the transmission power.

In addition to this justification [START_REF] Ochoa | Evaluating LoRa energy efficiency for adaptive networks: from star to mesh topologies[END_REF] shows that the optimization of energy can only be done by a strict spatial re-use by using the orthogonality property of the spreading factors.

According to [START_REF] Sartori | Enabling RPL multihop communications based on LoRa[END_REF] routing algorithms like RPL are difficult to use in a LPWAN context on unlicensed bands. The strict legislation in terms of number of messages does not leave much space for algorithms requiring frames dedicated to the operation of the network. It is necessary to design new MAC layers that counterbalance these routing issues.

In order to design these MAC layers, it is important to carry out a rigorous theoretical and practical study of the isolation between the spreading factors and the influence on the properties of an associated MAC layer. Several articles have treated the theory as [START_REF] Lim | Spreading factor allocation for massive connectivity in LoRa systems[END_REF], we propose to complete this study by experiments in real environment.

Performance Analysis of Logical Isolation Between

Spreading Factors

Experience with Time Phase Collisions

Experimental Protocol. In order to prove the hypotheses advanced, we set up an experiment with 4 nodes, two transmitters and two receivers of End-Device type (Adafruit Feather [START_REF]Feather Hardware[END_REF] with HopeRF RFM95 transceiver [START_REF] Hoperf | The HopeRF RFM95 Transceiver User Manual[END_REF]). We seek to study the impact of a simultaneous emission of two nodes on the same frequency band but with different spreading factors. The choice to use four nodes makes it possible to group them in pairs with the same parameters, one node in transmission and the other in reception. By analyzing the received frames and what they contain, we can deduce the frame error rate (FER) and compare it with the same rate without simultaneous emissions. The synchronization of the nodes is very important to finely control the phase shifts between the two transmitting nodes. Thanks to this synchronization, we can select a large frame and a small frame to analyze if the rate varies according to the crush zone of the packet. In order to achieve this synchronization, we connected the two transmitters by two wires and two Boolean signals. Figure 3 shows the wiring of this synchronization. One node is master and the other slave, the master waits for the first signal of the slave which indicates to him that he is ready to emit.

Once the master is ready to transmit and has received the signal from the slave, it sends a signal to the slave to tell him to start transmitting the frame (Fig. 2).

When the SF is increased by 1, the size of the packet is approximately doubled. We chose to use one package with a SF of 9 and another of 7. The packet sizes are respectively 250 ms and 70 ms. These sizes make it possible to take the longest packet as a reference and to crush it (disrupt it or collide it) by shifts by the second. This experiment was carried out in these realistic conditions that is to say that the two transmitters were side by side in one side and the two receivers on the other side. The two couples are separated from a distance of 200 m with a building in between. The distance of 200 m seems weak but given the indoor conditions of the nodes, we noticed by the practice, that we were in limit of reach for the link to SF7 which is the least robust. We have observed in practice and it is explained in [START_REF] Croce | Impact of LoRa imperfect orthogonality: analysis of link-level performance[END_REF] that in the near field there are orthogonality problems between SF. We decided not to do the measurements in this topology which is not representative of reality.

Simultaneous transmission of frames at the same frequency but with different spreading factors

Results. The experiment consists of sending 500 frames for a fixed time offset between the frame at SF 9 and that at 7. We decided to send 500 packets in order to have a correct estimate of the frame error rate. We have selected these values for the time offset so as to test crashes (overlaps or collisions) on different parts of the packet. This proves that this overwriting property is valid on all parts of the packet (Table 3).

Analyse. The frame error rate is very low and uniform whatever the area of the packet, this allows us to demonstrate that it is possible to send several frames simultaneously at the same frequency, with the same parameters but with a different SF. This physical isolation makes it possible to assert that it is possible to create physical channels on the same frequency that have different characteristics in terms of reliability and throughput. This physical isolation is not dependent on a time synchronization between the different channels and is not dependent on the content of the frame.

Collision Matrix on All Spreading Factors

Experimental Protocol. After proving that for a given pair of spreading factors (7 and 9), there is a real tightness at the physical channel level, it is necessary to generalize this property. For this, we place ourselves in the same experimental conditions, with two transmitters synchronized by logic signals, and two non-synchronized receivers. We will build a collision matrix. For this we parameterize a transmitter/receiver pair with a SF1 SF and the other pair with SF2. Then under these conditions, we re-test all possible time offsets.

Results. Table 4 is an example of a result for a delay of 10 ms between the two transmitters. The numbers are very similar regardless of the delay, so showing only one sample is enough. Analyse. For the diagonal of the matrix of the array Table 4, when the two emitters use the same SF, we notice that there are many collisions. We can not conclude that there is a tightness when two transmitters speak simultaneously with the same SF. When the two nodes emit with different SFs, the number of collisions is limited. It can happen, with a rate of 2.2%, that one of the two messages is not received by the receiver. Things

The results presented in this paper show that the LoRa™ physical layer proposes several levers that make it possible to envisage new MAC protocols that benefit from the characteristics of this mode of transmission. In view of what has been described above, we propose a new concept of 3-dimensional MAC layer, using the three frequency, time and code multiplexing, illustrated by the Fig. 4. The first two multiplexes (frequency, time) are relatively conventional, they are used by most technologies. Frequentially, the selected band, for example the 868 MHz ISM band, can be subdivided into frequency channels with a fixed (as in LoRaWAN) or variable bandwidth, in order to better use the properties of the LoRa™ modulation. In this case, higher bandwidths will allow links with higher throughput for short-range communications. On the second (temporal) multiplexing, we have seen in the experiments that the othogonality of the links does not depend a priori on a strict synchronization. However, it is necessary to synchronize the nodes constrained in energy; the Listen Before Talk technique can help limit temporal collisions. On these two first multiplexings, we are finally in a standard case of multi-channel MAC where it is possible to apply the algorithms of this domain (with or without an appointment, with or without a dedicated channel, etc.). What the LoRa™ technology allows to add, is that for a given channel {frequency, temporal}, a communication can be realized via a SF whose value will have an impact on the robustness and the range of the link. In addition, SF being orthogonal, several links between several objects can be made at the same time on the same channel {frequency, temporal}. The object can, for example, start with a low value of SF and attempt a communication with the target gateway. If he can not reach his recipient, after several tries, he can increment his SF and retry to connect. Once the connection is established, the gateway can record the parameters of the transmission in order to respond to the transmitter with the same parameters. The transmission will be more and more robust until you succeed. In this way, a node will be able to adapt its transmission technique to the quality of the link and/or its distance. The Fig. 4 represents this type of 3-dimensional multi-channel MAC. The different colors represent the SF used by a sending node. During the initialization phase of a node and dynamically during its lifetime, the node is colored according to the state of the link between it and the gateway. If the link is degraded, the node will change its settings and change color to a darker color. In the Fig. 5 one observes an example of topology of a MAC multi SF. It is interesting to see that depending on the zone in which it is, the node will have a different SF setting. The node number 4 is very far, it uses a high SF like the node number 1. By cons this node number 1 is much closer in terms of distance. It must surely be in a difficult environment (deep indoor, behind an obstacle between him and the gateway for example...). These solutions are made possible by the fact that a gateway has the possibility of receiving several SF without having to change configuration. This is generally not the case for End Devices, which, for ad-hoc communications between objects, requires to think of another strategy. These few solutions are to be developed later, but have been made possible by the metrology phase that we have just presented.

Conclusion

The LoRa™ technology may seem very close to the usual modulations of the IEEE 802.15.4 historical standard, but because of its intrinsic parameters and its context of use, it must lead to rethink the MAC and network layers to much higher topologies star or mesh with two hops. The context of the Internet of Things and LoRa™ defines transmissions in a very dense environment as transmission distances are high. This paper permit to define the main mecanisms which can be exploited in order to answer the problem of distribution of nodes in well disjoined channels. This preliminary work opens the way for many perspectives, such as to propose an original and efficient MAC layer for IoT. In order to overcome the constraints related to the duty cycle imposed by the standardization, it lacks a final tool to define concerning the detection of occupancy of the channel as that used in the well-known CSMA/CA. LoRa™ uses a type of modulation that allows transmissions above the noise level. The RSSI measure is no longer a valid indicator of channel occupancy. The LoRa™ tranceivers integrate a socalled CAD (Channel Activity Detection) mechanism which makes it possible to detect a coherent preamble, the preamble of a message with the same SF. We are currently working to propose a MAC called CSMA/CAD without temporal constraint linked to a duty cycle.

Fig. 2 .

 2 Fig. 2. Synchronization of transmitters by wire

Fig. 4 .

 4 Fig. 4. Channel multiplexing on the time, frequencies and by code

Fig. 5 .

 5 Fig. 5. Topology of a multi spreading factor MAC (Color figure online)

Table 1 .

 1 Range of spreading factors from datasheet[START_REF]Semtech: Datasheet of Semtech sx1276 LoRa™ tranceiver[END_REF] LoRa™ Demodulator SNR -5 dB -7.5 dB -10 dB -12.5 dB -15 dB -17.5 dB -20 dB

	SpreadingFactor	6	7	8	9	10	11	12
	Chirps/symbol	64	128	256	512	1024	2048	4096

Table 2 .

 2 Set of coding rate from datasheeet[START_REF]Semtech: Datasheet of Semtech sx1276 LoRa™ tranceiver[END_REF]

	Cyclic coding rate 4/5 4/6 4/7 4/8
	Overhead ratio	1.25 1.50 1.75 2

Table 3 .

 3 Estimate of FER on an emission of 500 frames per measurement point.

	Delay 2 frames ok SF9 frame ok SF7 frame ok FER
	0 ms	494	0	6	0.012
	77 ms 489	0	11	0.022
	154 ms 475	0	25	0.05
	231 ms 490	0	10	0.02

Table 4 .

 4 Spreading factor matrix for 10 ms delay

	sf1	7	7	7	7	8	8	8	8	9	9	9	9 10 10 10 10
	sf2	7	8	9 10	7	8	9 10	7	8	9 10	7	8	9 10
	ok	0 500 488 497 497	0 484 500 489 489 37 489 487 491 495	8
	1 ok	49	0 12	3	3 18 16	0 11 11	6 11 13	9	5 16
	error 205	0	0	0	0 449	0	0	0	0 456	0	0	0	0 474
	nok 246	0	0	0	0 33	0	0	0	0	1	0	0	0	0	2


Adrien Van Den Bossche
email: adrien.van-den-bossche@irit.fr

Réjane Dalce
email: rejane.dalce@irit.fr

Nicolas Gonzalez
email: nicolas.gonzalez@irit.fr

Thierry Val
email: thierry.val@irit.fr

LocURa: A New Localisation and UWB-Based Ranging Testbed for the Internet of Things

Keywords: Ranging protocols, Time Of Flight, Testbed, Indoor Localisation

As many applications of the Internet of Things assume the knowledge of mobile object position, localisation has become a hot topic in the academic research community as well as for industrial R&D departments. Although distance measurements (ranging) and localisation can be studied though simulations, using real nodes provides more accurate and realistic results, especially when the nodes are deployed in the target environment. In order to support this effort, the paper presents LocURa4IoT, a new Localisation and UWB-based Ranging testbed for the Internet of Things. The testbed is made of 20 nodes based on Decawave DW1000 UWB-based transceiver and Arduino-compliant micro-controllers. The nodes' control infrastructure is presented in the paper, as well as a few results obtained with LocURa. Two open datasets are also published with the paper.

I. INTRODUCTION

Wireless networks have come a long way from their humble beginnings as mere extensions to existing wired networks. As the performance increased, these networks evolved and became an integral part of day to day human operations. Wireless Sensor Networks soon followed, accompanied by MANETs and VANETs. The addition of communication abil-ities to everyday objects gave birth to the Internet of Things (IoT) which is now poised to revolutionise all aspects of human life. This type of huge networks is expected to generate humongous amounts of data which will be fed to applications in various domains such as transportation, health, trade etc. In order to be useful, the produced data must be tagged with, at least, a timestamp and a location. Indeed, while knowing that the temperature in a room is 50°C is a significant piece of information, it does not help much if the room cannot be identified. This localisation issue is not new: in outdoor environments, GPS signals are massively used. Unfortunately, indoor environments often defeat this solution due to the presence of numerous obstructions. Hence, indoor localisation has been a competitive research field for the last ten years, both for the academic research community and the industry.

Just as wireless networks evolved through extensive study and experimentation, indoor localisation requires prototyping tools that are accessible to all researchers. Given this requirement, this paper introduces LocURa, a testbed dedicated to the study of Time Of Flight (TOF) based localisation. This platform allows the fast prototyping and evaluation of communication and ranging protocols as well as localisation algorithms in a real indoor environment.

The paper is organised as follows: after detailing the objective and identifying relevant criteria, a review of the existing tools is conducted. The proposed testbed architecture and components are then introduced. Results from a few use cases are presented. Finally, the conclusion and evolution perspectives are presented.

II. CONTEXT

While it is possible to address the localisation issue using various signals, measuring the TOF between a pair of nodes has been one of the most reliable and precise solutions.

Although the received power level, which can be expressed as a Received Signal Strength Indication (RSSI), is readily available on most radio platforms, it is strongly challenged by fading phenomena in dynamic indoor environments [START_REF] Gui | RSS-based indoor localisation using MDCF[END_REF]. Using the signal's Angle Of Arrival (AOA) could significantly reduce the number of reference nodes but the hardware constraints are often prohibitive for small form-factor devices (antenna arrays...). In order for the TOF to be relevant, the system requires the ability to measure very short durations with high precision: this involves high resolution timers dedicated to timestamping radio events. Ultra-Wide Band (UWB) technology is the best candidate for such measurements since its high bandwidth allows for high distance resolution [START_REF] Ghavami | Ultra wideband signals and systems in communication engineering[END_REF].

While IEEE 802.15.4-2011 UWB-compatible transceivers became available, mathematical models have been designed in order to evaluate performance through simulations. One key advantage of simulations is repeatability: with a limited cost, it is usually possible to run the same experiment hundreds of time. This process allows the identification of trends in the system behaviour. Unfortunately, as this technology supports both data and ranging (distance measurements), the evaluation platform must also take various physical parameters into account:

-propagation conditions, -signal reflections on walls, ceiling, other radio devices, -impact of obstructions of various types and presence of Line Of Sight (LOS) and non-LOS links, -impact of PHY-level clock synchronisation, -PHY-level clock skew, -impact of node temperature on performance, as said temperature is influenced by the communication protocol's states (reception, idle, transmission...), -influence of antenna orientation and directivity, Modeling all these phenomena is a complex task. Having to configure all these parameters for a single simulation and interpret the results would be even more daunting. Thus, it is preferable to have a real world testbed for the evaluation of the proposed solutions. By replicating the target environment, it is possible to predict to a certain degree the behaviour and performance of the protocols and/or algorithms. Such a testbed, in addition to giving access to UWB devices, should offer well known services such as:

-local and 24/7 remote access, -experiment management tools:

dynamic node configuration, -individual and bulk firmware upgrade, -scenario execution and repetition, -environment parameters records (temperature, humidity...), -predefined data processing tools and scripts, -datasets download interface. A few nice-to-have features would include:

-live-access to the data produced: dashboards would help keep track of specific criteria, -node mobility, -live video stream associated to the experiment: this would allow to correlate the experimental results with uncontrollable events occurring on site.

Within such an environment, results repeatability will be easier to investigate: from the user's point of view, launching hundreds of experiments will be as easy as running a hundred simulations. Intensive use of the platform brings the need for it to be as cost effective as possible: the hardware components should be affordable while the pieces of software used should come from the open-source ecosystem. In addition to reducing costs, this last point ensures that the tools are reviewed by a significant community and can then be trusted. These characteristics make it possible for other research teams to replicate the testbed with a reasonable investment: these sister platforms could be deployed in specific environments (mines, tunnels...). On the other hand, the existing testbed can be useful to other researchers who are more interested in algorithms and data processing: the datasets generated during experiments can be made available to colleagues from other research facilities in order to compare new algorithms and inspire new protocols.

Given the requirements outlined in the previous paragraphs, the next section will review the existing platforms for reliable TOF-based ranging and protocol testing.

III. RELATED WORK

In order to facilitate the prototyping and evaluation of new ranging protocols and localisation algorithms while ensuring a certain level of confidence in the results, a physical test platform is required. In [START_REF] Van Den Bossche | DecaDuino: An Open Framework for Wireless Time-of-Flight Ranging Systems[END_REF] an UWB-based radio node De-caWiNo and the corresponding libraries were introduced. Both the hardware and software were published under an opensource license in order to grant fellow researchers the ability to modify the hardware and software platform. Using the provided primitives, new communication protocols as well as ranging protocols can be implemented on the devices. While DecaWiNo requires the user to delve into the code, other UWB-enabled commercial platforms such as [START_REF] Timedomain | [END_REF], [START_REF]InfSoft[END_REF] and [START_REF] Uwinloc | [END_REF] offer access to the measurement results. TimeDomain offers a development kit which allows reconfiguration of the nodes: for example, either TDMA or Aloha MAC can be selected. Nevertheless, based on the information we obtained, modification of the source code is not allowed. InfSoft's approach to indoor localisation is quite different: the company uses its expertise to design a customised product for the client, using various radio technologies (UWB, BLE, WiFi...). The software responsible for interpreting and displaying the data is also provided by InfSoft.

It is apparent, from this brief review of the existing radio devices, that, whether the user wants to tinker with of just obtain standardised data from the network, an off-the-shelf solution exists. Unfortunately, this is not enough if the goal is to extensively study the localisation problem. As a matter of fact, running a single experiment is meaningless: random environmental influences may be to blame (or praise) for the results. Therefore, repeatability is an important aspect of experimentation. Said repeatability requires a structured testbed which can automatically run experiments a number of times and feed multiple datasets to other algorithms. Large scale IoT testbeds flourish around the world. Two of the most well-known testbeds are FIT IoT-Lab [START_REF] Fleury | FIT IoT-LAB: The Largest IoT Open Experimental Testbed[END_REF] and SmartSantander [START_REF] Sotres | Practical Lessons From the Deployment and Management of a Smart City Internet-of-Things Infrastructure: The SmartSantander Testbed Case[END_REF]. In order to fuel the use of experimentation facilities among the scientific community, the end users and service providers, the SmartSantander project offers an access to its platform which consists in a variety of sensors deployed in a smart city, organised in a three-tiered fashion: IoT nodes sense the environment, repeaters forward the data from/to IoT nodes through 802.15.4 DSSS links and gateways allow information exchange between the IEEE 802.15.4 network and other technologies (Wi-Fi, GPRS/UMTS, Ethernet).

FIT IoT-Lab offers remote access to sensor networks deployed at six different locations across France. Upon registering, users may launch experiments and retrieve the data produced by the nodes. Although most of the nodes only implement IEEE 802.14.5 DSSS radio communications, the platform allows the integration of other technologies, as long as the proposed module implements a required python class. Finally, mobility [9] is supported by the use of robots such as the Turtlebot2 and the Wifibot. At the moment, only fixed circuit-based mobility is available but user controlled mobility and model-based mobility are being implemented.

The proposed infrastructure in both testbeds enables great control over the experiments but, unfortunately, the radio technology is not suitable for precise localisation: being narrowband, 802.15.4 DSSS does not support fine distance resolution.

The fact that most large-scale testbeds employ 802.15.4 DSSS has motivated researchers to create their own UWBenabled setups. In [START_REF] Vashistha | Self Calibration of the Anchor nodes for UWB-IR TDOA based Indoor positioning System[END_REF], autonomous anchor calibration is studied. Tag localisation is the focus in [START_REF] Ling | High Precision UWB-IR Indoor Positioning System for IoT Applications[END_REF] while [START_REF] Bonizzoni | UWB Tracking for Home Care Systems with Off-the-Shelf Components[END_REF] aims at enhancing the performance of fall detection solutions by localising the monitored elderly and providing the companion robot with the position where the suspected fall took place. Unfortunately, in addition to using homemade devices, the testbeds used in [START_REF] Vashistha | Self Calibration of the Anchor nodes for UWB-IR TDOA based Indoor positioning System[END_REF] and [START_REF] Ling | High Precision UWB-IR Indoor Positioning System for IoT Applications[END_REF] involve heterogeneous node architectures, i.e. the tags can only perform transmission and not receive data. Although the concern for energy consumption is perfectly valid, such testbeds' usability is quite limited. In the case of [START_REF] Bonizzoni | UWB Tracking for Home Care Systems with Off-the-Shelf Components[END_REF], IEEE 802.15.4-2011 compliant hardware is used (Decawave EVB1000 [START_REF]Decawave products[END_REF]) but the objective so far is not to provide a platform for other researchers to test their own solutions. We can only conclude that a suitable testbed for precise indoor localisation is yet to be found.

IV. LOCURA4IOT: A NEW LOCALISATION & UWB-BASED RANGING TESTBED FOR THE IOT

A. Nodes Description

The LocURa testbed is based on DecaDuino [START_REF] Van Den Bossche | DecaDuino: An Open Framework for Wireless Time-of-Flight Ranging Systems[END_REF], an open framework for the fast-prototyping and performance evaluation of UWB-based protocols. DecaDuino provides a driver for the DecaWave DW1000 UWB transceiver and others modules based on this transceiver, such as DecaWave DWM1000 [START_REF]Decawave products[END_REF]. In addition to wireless communication, DecaDuino supports ToF ranging. Since this framework was designed to aid in the implementation of TOF based protocols, DecaDuino also provides access to the Physical-level 64GHz high precision timer which offers precise message timestamping at both transmission (t T X ) and reception (t RX ) with a resolution of 15.625ps. Finally, DecaDuino implements advanced synchronisation/timestamping features described in the IEEE 802.15.4-2011 standard, such as delayed transmission and receiver skew evaluation. The internal transceiver temperature of each node is also available on the testbed: this parameter generally has a significant impact on the synchronisation processes, impacting the frequency stability of cost-effective quartz.

A compliant hardware called DecaWiNo is also described in [START_REF] Van Den Bossche | DecaDuino: An Open Framework for Wireless Time-of-Flight Ranging Systems[END_REF] and shown in Figure 1. On this design, the transceiver is a DWM1000 [START_REF]Decawave products[END_REF] and the Arduino-compliant board is a Teensy 3.2 which embeds an ARM Cortex M4 32-bit MCU rated at 72MHz, with 64kB RAM and 256kB program memory. DecaWiNo follows an open hardware design; various resources on this node can be found at [START_REF]DecaWiNo and DecaDuino ressources[END_REF]. There is no specific Operating System deployed on the micro-controller of the node; all protocol operations have been implemented in C.

B. Testbed Description

The LocURa testbed is made by three layers: the lower layer is the Wireless Sensor Network (WSN) used for the experiments. The second layer is the Controller layer: as The LocURa WSN comprises 20 DecaWiNos deployed in a single 100 square-meters room. The walls are either made of terracotta bricks or drywalls. The 20 nodes are deployed on a single horizontal plane which is 2.65m from the floor and created using a PVC structure, as shown on Figure 2. The position of the nodes (antenna position) has been measured using laser telemeters during the installation with an accuracy under 1cm. At this time, two mobile nodes are positioned on two motorised rails respectively 2 and 7 metres long; linear position, speed and acceleration of the mobiles can be controlled from the experimentation scenarios; the 2D-positions of the mobiles are available in real-time using the stepper-motor feedback, with a 1mm accuracy. The real mobile position can be exploited in the results to compute ranging/localisation error. Figure 3 represents the room and the 3 nodes (0x20, 0x24 and 0x2F) involved in the experiments presented in section V. In this configuration, the maximum distance on the platform between two nodes is 10 meters (in outdoors measurements, the same radio devices were able to communicate at distances up to 30 meters). Thanks to the disposition of the walls, some links are NLOS (Non Line-of-Sight), as we will see in the next section of the paper.

As is usually the case with testbeds, the experiments are managed by a central server that enables remote node programming (flashing) and log centralisation. The nodes are managed by cost-effective controllers based on Rasberry-Pi. The controllers provide both flashing/reprogramming services and logging of the serial output of the nodes via USB cables. Controllers are synchronised via Precision Time Protocol (PTP, IEEE 1588) over Ethernet to enable a homogeneous console log among controllers. With a precision of a dozen microseconds, PTP is not suitable for TOF/TOA indoor ranging operations: the 64GHz timers embedded on the DecaWino nodes are used for this purpose. Using PTP timestamps, the logs are merged and the result is available on the testbed server.

Node behaviours are described using Arduino sketches and the interaction between the nodes, the experimentation scenario, is described with a python script. Within this script, a basic experiment can be run once or multiple times. Since the script also controls the rail, an experiment can be used to study the impact of various protocol parameters in the presence of node mobility.

Live access to the nodes' input/output console is also possible via the MQTT protocol: this enables real-time processing (localisation algorithms...) in a typical IoT-fashion, using popular IoT tools such as Node-RED or MQTT Python agents. For example, Node-RED is used to compute the ranging error for each estimate published on MQTT: this error is then appended to the ranging data and published on the MQTT bus (see datasets provided in section V of the paper).

Finally, while providing a public access to the testbed is a perspective we are actively studying, it is not the only open approach we are considering. As a matter of fact, the testbed has been developed by using cost-effective and open-source hardware and software to enable its open dissemination [START_REF]DecaWiNo and DecaDuino ressources[END_REF].

In addition, we intend on making the datasets created using our own testbed and experiments available to the research community in formats that allow easy processing using Python. The next section will describe a few of those experimental results.

V. PLATFORM USAGE AND RESULTS

In this section, we present several experimentation scenarios and results obtained using the LocURa testbed.

A. Transceiver Temperature Impact on Clock Skew

The clock skew usually has a significant impact on the synchronisation process, and thus, the ranging error. The generalpurpose quartz (10ppm) typically used on cost-effective wireless nodes are mainly impacted by the temperature variation. The UWB reception process causes heavy computation by the transceiver, implying a high energy consumption (300mW) and a temperature increase during long reception periods.

In experiment #1, we ran two scenarios involving two nodes, A and B. In both scenarios, node A sends frames at a rate of 10fps as in a typical beaconing protocol, during 500s (5000 frames). A's transceiver is in idle mode between two transmissions and does not listen to the medium between two frames. In scenario #1a, node B runs a continuous RX mode: upon receiving a frame, B evaluates the difference (skew) between its own clock and A's using the clock skew evaluation function of DecaDuino. B also tracks its own temperature. In scenario #1b, node B runs a 10ms slotted RX mode (and then is in idle mode during 90ms) for the 2000 first frames, then returns in continuous RX mode for the last 3000 frames. From a network point of view, the first part of the experiment corresponds to beacon tracking in a WSN while the second part fits in an ad-hoc scheme where nodes may be solicited at any time. Figure 4 represents the skew evolution for the two scenarios #1a and #1b, for each message. As we can see, for scenario #1a, the absolute skew is minimal at the beginning of the experiment and then the clock difference increases pretty quickly. In scenario #1b, the clock difference is relatively stable for the 2000 first frames, when the slotted RX mode is activated. As soon as the continuous RX mode is activated, the clock difference increases sharply.

Figure 5 represents the clock skew distribution vs the normalised temperature of node B. The reference temperature is defined as node B's temperature at the beginning of the experience. As we can see, the receiver temperature has a direct impact on clock skew, which impacts the ranging accuracy, as we will see in the next experiment. In experiment #2, we compare two well-known ranging protocols: Two-Way Ranging (TWR) and Symmetric Double-Sided Two-Way Ranging (SDS-TWR) (Figure 6). While TWR is simpler and only requires 3 messages, the clock skew between the two nodes impacts the ranging process because timestamps t 2 and t 3 are not obtained with the same clock (server's clock) as t 1 and t 4 (client's clock). Thanks to the symmetry in the 4-message exchange, SDS-TWR protocol is more robust than TWR. In [START_REF] Dalce | Reducing localisation overhead: a ranging protocol and an enhanced algorithm for UWB-based WSNs[END_REF], we have proposed a correction method based on the skew value available from DecaDuino. This correction (TWR-skew) improves the ranging results obtained from the original TWR. In experiment #2, the 7-meter long rail is used to move the mobile node 0x2F (server) while ranging with fixed node 0x20 (client) is taking place, using SDS-TWR. A total of 1300 range estimates have been collected in this experiment. The timestamps t 1 , t 2 , t 3 , t 4 , t 5 and t 6 , the skew and the nodes' temperature have been logged into an open dataset [16]. TWR has been extracted from the same dataset, considering only timestamps t 1 , t 2 , t 3 and t 4 . The real distance has also been included in the dataset, enabling the computation of the ranging error.

Figure 7 shows the ranging error for each protocol. As we can see, using TWR-skew leads to as good a performance as with SDS-TWR while saving 1 message. The dataset has been published to encourage the reuse of the experiment's results. In this experiment, the 7-meter long rail is used to move the mobile node 0x2F (client) while performing ranging with the fixed node 0x24 (server). Due to node placement in the room, the link between 0x24 and 0x2F can either be LOS or NLOS, depending on the rail course: in the interval [0m, 3.40m], the radio link is in hard-NLOS because of the wall angle (material used: terracotta bricks); in the interval [3.40m, 7m], the link is LOS. Figure 8 illustrates the deployment of nodes 0x24 and 0x2F during experiment #3. For this experiment, TWR protocol ran 1047 times. The mobile speed was set to 3.3cm/s.

The dataset [17] of this experiment is available online. Figure 9 illustrates the raw NLOS indicator value vs. the rail course. As we can see, the proposed indicator is quite relevant, even without averaging. Considering a threshold value equal to 9, the hard-NLOS situation is correctly detected 93% of the time. In the testbed's current state, two nodes are mobile: a scriptcontrolled rail is used to move each on a defined axis in the room. Data generated by the experiment is collected via USB by RaspberryPi 3 units, which are responsible for publishing the content on an MQTT bus over an Ethernet network. This MQTT bus is also used to send commands to the various devices: this enables a high level of automation for the experiments. While all the data is logged, the testbed also offers a live feedback on the experiment (node position, ranging error and so on) though a GUI based on Node-RED.

Finally, using three studies, we have illustrated the use of the platform.

Having such a tool is an opportunity for the entire community: while it gives us the ability to test our protocols on a real platform, it also produces data that can be shared with other researchers. The next step is to give remote access to fellow researchers. We are also working on including other mobile nodes (secondary rails) as well as nodes which can rotate on an axis. Some of these nodes will be placed in our anechoic chamber: this will allow comparative studies and investigation of the environmental impact. New fixed nodes will also be deployed in the main testbed room: they will be placed at a different height in order to support 3D-localisation. Finally, we will update part of our deployment with the latest generation of transceivers: with this new hardware, we plan on coupling TOF and Angle Of Arrival localisation.

Fig. 1 .

 1 Fig. 1. DecaWiNo: a Deca-Wireless Node

Fig. 2 .Fig. 3 .

 23 Fig. 2. The testbed room On the platform, from a network point of view, all nodes

Fig. 4 .

 4 Fig. 4. Skew Evolution for experiment #1a and #1b

Fig. 5 .

 5 Fig. 5. Skew vs. Transceiver Temperature in Experiment #1

Fig. 6 .

 6 Fig. 6. TWR and SDS-TWR protocols sequence diagram

Fig. 7 .Fig. 8 .

 78 Fig. 7. Ranging Error vs Distance, for each protocol

Fig. 9 .

 9 Fig. 9. NLOS Indicator vs. Rail Course Figure 10 represents the ranging error vs the rail course. Using the NLOS indicator, erroneous range estimates can be avoided. The challenge consists now in proposing a correction model to deal with NLOS links. The open dataset can be used in this objective.

Fig. 10 .

 10 Fig. 10. Ranging Error vs. Rail Course

ACKNOWLEDGMENT

The testbed has been created thanks to a FEDER/French Occitanie Région grant with the GUINNESS project. The testbed is located in the research lab at the Institut Universitaire de Technologie (IUT) de Blagnac, University of Toulouse Jean-Jaurès, France.


Hasan Alkhatib

Marcel Pasquinelli

Ludovic Escoubas

Jean Jacques Simon

Pascal Pierron

Ben Sadok

Dkhil

Lifetime of inkjet printing OPV modules

UMR CNRS 7334, Universités d'Aix-Marseille (AMU) et de Toulon (UTLN) -www.im2np.fr H. ALKHATIB 1 , M. PASQUINELLI 1 , L. ESCOUBAS 1 , J-J. SIMON 1 , P. PIERRON 2 , S. BENDKHIL 2 1 IM2NP UMR 7334 -AMU -Marseille, France --2 Dracula Technologies -4 rue Georges Auric, 26000 Valence, France LED ceiling lamp (2100 lm, 6500 K, 17 W)

Harvesting energy from their environment could be an ideal solution for an autonomous function of numerous small electronics. Organic Photovoltaic (OPV) cells are a promising technology for next generation photovoltaic cells combining novel properties such as light weight, flexibility, or color design with large-scale manufacturing with low environmental impact. Furthermore, the OPV cells are good solution for Indoor applications. In this field, DRACULA TECHNOLOGIES (DT) has developed inkjet printing organic solar cells and modules. The great advantage of inkjet printing as a digital technology is the freedom of forms and designs, large area organic modules with different artistic shapes. The stability of OPV cells are critical element for up-scaling and commercialization of this technology. To evaluate the stability and lifetime of the DT modules, the ISOS-D-1 (shelf lifetime) protocol is applied for 175 days. The devices were stored under dark ambient conditions and a LED light source is used for the periodical characterizations.

One of the specifications required for OPV cells market is the stability of the devices. The diffusion of oxygen and moisture through the encapsulation system is the main factor responsible of the device degradation. However, the obtained results confirm the adaptability of inkjet printing OPV modules to powered small electronics, as in IoT (Internet of Things) applications, at low illumination indoor environment.

  Degradation curves of Isc (normalized to the initial value at time = 0) for 3 Illumination levels.Degradation curves of Voc (normalized to the initial value at time = 0) for 3 Illumination levels. acknowledge Dr. Damien BARAKEL (IM2NP IRM-PV) for his contribution in the LBIC mapping.Degradation curves of the fill factor (normalized to the initial value at time = 0) for 3 Illumination levels. Beam Induced Current) mapping (in 2D and 3D) of the presented module at time = 175 days.