Sylvain Cherrier

Yacine M Ghamri-Doudane

The "Object-as-a-Service" Paradigm

Keywords:

The increasing interest about the Internet of Things (IoT) is almost as remarkable than its practical absence in our everyday lives. Announced as the new breakthrough in IT industry, the domain is characterized by a large number of architecture propositions that are in charge of providing a structure for applications creation. These architectures are needed because of the heterogeneity of stakeholders involved in IoT Applications. Programming languages, operating systems, hardware specificities, processing power, memory, network organization, characteristics, constraints, the world of IoT is so diverse. Furthermore, these architectures should provide an easy access to users that are not aware of IT technologies involved. The Services Oriented Computing (SOC) has shown in the past its relevance to the decoupling constraints interoperability among stakeholders. The composition of loosely coupled services facilitates the integration of very varied elements and provides agility in the creation of new applications. But unlike the approach inherited from the SOC in pre-existing services are composed to obtain a specific application, we propose a more dynamic notion of service. Our "Object-as-a-Service" point of view is based on the notion of building dynamically the service needed on each Object and then integrate it in the whole composition. This paper focus on the gain of this approach for the IoT by promoting the "Object-as-a-Service" paradigm as a basis for the creation of dynamic and agile user-made applications.

I. INTRODUCTION

With the spread of wireless communications and the rise of the number of devices capable of processing data, the idea of connecting everything to everything, through the universal medium offered by the Internet, opens the way to a new era in the computing domain, usually called the "Internet of Things". The "Major trends in computing", as defined by M. Weiser [START_REF] Weiser | The coming age of calm technology[END_REF] has occurred. At the beginning, the "mainframe" era (one computer for many users), followed by the "personal" era (one computer for one person), we are now entering the "ubiquitous" computing era (many computers for one user). Desktop computers, laptops, but also smartphones, palm, internet Boxes, and now connected TVs, household appliances, phydgets, single-board microcomputers, we are surrounded by "smart" objects, able to process data, communicating through networks, and having new capabilities of sensing or acting on the real world.

The main idea of the Internet of Things is to expand the network, extending it into houses, buildings (walls, floor, windows, doors, etc.) and cities (car park, traffic light, lights, etc.). After its connection to offices, then homes, the Internet The "Object-as-a-Service" architecture. A service (at the bottom of this figure) runs on the Object, using its functionalities (sensing, actuating, computing). This specific service is dynamically created and tailored for user's need, on-the-fly, following the description given by the user on the programming layer (the top service of the figure) offered by this Object. now connects farther, to the Objects. But for what purpose? Do we really need this Objects interconnection with the public network? Users will want applications to take advantage of their objects and their new capabilities: measuring the real world and acting on it, processing informations, and communicating with the network. Automatically. Without effort. Easily.

Creating applications for the IoT is not an easy task, because stakeholders are very varied, with multiple and very different constraints. The idea of using a Service approach (proposed by Services Oriented Computing, SOC) can facilitate this integration. Combining services is a way to easily create applications.

Our approach calls for this Service vision of an object. But we go further. Usually, the Service provides an access to the data, for example the sensed measure of a physical data (or to an action, in the case of an actuator). We advocate a generic system that allows us to understand the object as a dynamically built services provider. This means that the object must provide the user a way to describe the service to be rendered (see Figure 1). In the manner of "application server" 1 , we would like to consider each object as a computer that can be remotely programmed. Objectas-a-Service (OaaS) is an approach in which we can define and create, on-the-fly, new original services on each object, dynamically. OaaS gives the ability to remotely program an Object in order to include its actions in a global set of interactions.

This position paper is organized as follow: Section II presents the interest of Services for the IoT. Section III lists and defines the different elements usually found in IoT architecture. A classification model of IoT architectures is proposed in Section IV, in which some contributions are classified and compared (including OaaS). Finally, concluding remarks are given in Section V.

II. SERVICES IN IOT A. The needs

Most papers describing the IoT offer impressive figures about the number of objects connected to the Internet within a near future [6] [12] [14]: already, the number of objects connected to the Internet exceeds the number of users, and there will be between 16 to 50 billions devices2 connected in 2020.

The main modes of use of these objects are limited at the moment to simple remote controls. The user accesses his Objects through his smartphone, gathering data collected, or triggering actions on them. But this is a narrow conception of IoT, in which the Internet part is used for the universal connectivity it provides. From our point a view, the interest of IoT increases when Objects interact with each others, without human intervention. As introduced by M. Weiser in his reference article [START_REF] Weiser | The coming age of calm technology[END_REF], the "calm computing" should hide the complexity of electronic devices settings. It should even hide the need for a human to be involved in the chain of reactions. IoT applications should seamlessly analyse sensed data and drive actions on actuators following the global instructions given by the user, automatically and without his mediation.

As the number of connected devices increases, and because Objects can collect huge variety of data (or trigger actions), the possibilities offered for applications are wide. Unlike computers and their finally restricted number of different kind of peripherals (hard disk, keyboard, mouse, webcam), the combination of interactions and the diversity of the effects that a user may want lead to less generic applications than in the usual domain of data computing. We believe that a user will not easily find applications "offthe-shelf" fitting his needs, compared to office or home computing domain in which the proposed generic and "alreadymade" software are more adapted.

In facts, it seems difficult to imagine real "calm" 3 IoT applications "off-the-shelf". Generic applications won't be able to provide sufficient flexibility and adaptability. In the "Internet of data"4 , common use-cases mimic the user's way of consuming services as it was before the Internet arises: storing and accessing data, read and writing more or less structured informations, etc. The transposition to the Internet of services organisation and composition was quite trivial.

On the contrary, the IoT opens a new way of understanding interactions between services, especially because these services relate to the real world. Despite the fact that the global trend of proposed demonstration regarding the IoT are often limited to "remote control" of distant devices, we believe that there is a new and interesting approach: comparable to Machine-To-Machine, the IoT may propose seamless interactions between Objects, providing an automatic and pervasive control of the real world based on the user's needs.

For us, the future of IoT usages, or a part of these use-cases, is original. The needs of IoT users are varied, specific to each of them (individual or organization, home automation, smart building, smart cities) [START_REF] Perera | Sensing as a service model for smart cities supported by internet of things[END_REF]. The proposed solution of "off-the-shelf" applications, as in the "Internet of Data", is much more restricted. IoT Applications must be precisely configured according to user needs. In IoT usecases, the focus is on user's objects combination. Combinations settings take precedence over application algorithms (which are not very complicated in IoT domain, mostly actions and reactions to gathered data, or data computation). And these settings, and the objects on which they apply, are extremely varied. This is the reason why the proposal of "offthe-shelf" applications is less relevant, and that we plead for more adaptable and dynamic applications.

B. Applications creation issues

The main characteristic of IoT applications stands in the wide variety of elements that composes it. Besides their number, and the diversity and the specificity of the applications in which they are involved, Objects greatest feature is their heterogeneity.

Objects can be categorized depending on:

• Object's Physical constraints: number and type of varied importance (from an almost total absence of constraints to enormous constraints in terms of memory, processing power, and high energy resource limitation, depending on the type of object)

• Networks Constraints: high speed, with large payload, reliable, or unreliable, with low throughput and limited payload. Wireless Sensors and Actuators Network(WSAN), often integrated to the IoT, have lot of limitations. Their combined constraints (low throughput, limited energy and limited reliability) have serious consequences.

As a result, the user may experience difficulties in the creation of his specific application (lack of common tools, absence of generic platform). And if he succeeds, the application strong dependences on hardware, network and software infrastructures strongly limits its re-usability. Similarly, one can have serious doubts about its scalability, and its maintainability (that can even be impossible). For example, what happens in case of hardware failure and its replacement by another, equivalent, offering the same capabilities, but with different equipment?

These strong constraints (the disparity of hardware capabilities and heterogeneity of components) limit the creation and reuse of any creation. Development costs may be important, slowing the growth of the domain. The difficulty of creating custom applications must be solved.

C. Service approach in the IoT

The "Service" approach limits dependency between stakeholders by introducing loosely coupled links. By providing an interface describing the exchange and hiding its implementation (and its possible change or modification), the dependence of the consumer to the producer is shrinking. The service is provided universally, and the specificities related to the real hardware are hidden. Calls to the service, or calls between services, are executed in a standardized manner. This facilitates interactions and limits dependences to the mere compliance with the interface description. This approach has been successful in the Internet of Data, where no user wonders which kind of hardware or operating system is running the web service he is currently using.

As part of the IoT, using the services approach would accelerate the creation of applications by limiting it to generic services calls. It would also increase the scalability as the infrastructure, composed of many devices, may change continuously, according to the breakdowns and replacement of elements that constitutes it [START_REF] Sarkar | A scalable distributed architecture towards unifying iot applications[END_REF].

The "Service" approach allows the introduction of genericity and flexibility, and thus facilitate applications creation. Reusing a service in a new composition, creating new service, or making it evolves while offering the same interface, open new prospects for IoT applications maintenance and their easy evolution. IoT applications using Services approach become more hardware independent, and can be adapted to new needs.

D. Object-as-a-service

Introducing a Service approach in the IoT means to consider each Object as a Service Provider. This approach is presented for example by N. Priyantha et al. [START_REF] Priyantha | Tiny web services: design and implementation of interoperable and evolvable sensor networks[END_REF], D. Guinard et al. [START_REF] Guinard | Towards the web of things: Web mashups for embedded devices[END_REF] [START_REF] Guinard | Interacting with the soa-based internet of things: Discovery, query, selection, and on-demand provisioning of web services[END_REF] or E. Wilde [START_REF] Wilde | Putting things to rest[END_REF]. Usually, the Service proposed by authors gives an access to the data gathered by Objects (sensors), or a way to trigger actions on Objects (actuators). This data-oriented approach gives a "remotecontrol" vision of the Internet of Things. Many demon-Figure 2. The service approach is often structured as the left part of this figure, in which the service is only able to give access to data gathered by the sensor(or trigger an action on the actuator). On the right, the Objectas-a-Service service gives the user a way to explain his algorithm. Then, a dynamic service is build, using Object processing capabilities to execute the algorithm.

strations show a user gathering data from his home with his smartphone (temperature, energy consumption, alarm control centre), acting on it (open/close shutters, setting the central heating, etc), or a car driver finding an empty car park place. Then, we can imagine a central program that will use these services for managing a house, a smart building, some public services in a city, etc.

What we call "Object-as-a-service" goes further than mimicking the Data vision offered by "Service Oriented Computing" in the Internet of Data. The IoT domain could be an opportunity to evolve the concept of SOC to something more valuable. Rather than being limited to Objects sensing and actuating functionalities, the access to their processing capabilities is certainly a great evolution that IoT should offer. These processing capabilities are a great added value offered by connected Objects. Nowadays, these processing capabilities are mainly used for organizing the network, and implementing the different protocols at work to offer access to data or actions.

Giving remote access to the Objects processing capabilities opens the way to the dynamic definition of new services (Figure 1). This offers a wide latitude of creation. We propose to see each Object as an application server (such as Tomcat in the Internet), which allows deploying and managing an application on a remote server (Figure 2). Having this ability seems a promising path for the IoT. "Object-as-a-service" is the possibility to access and use its programming functions. OaaS is a service for creating new services.

OaaS can be done with a generic programming language, when they are available for Objects. For example, Maté [START_REF] Levis | Maté: A tiny virtual machine for sensor networks[END_REF], a virtual machine embedded in small Objects, can be programmed to accomplish new services. Darjeeling [START_REF] Brouwers | Darjeeling, a feature-rich vm for the resource poor[END_REF] is a version of an embedded Java virtual machine for that purpose. Our OaaS running solution is called D-LITe [START_REF] Cherrier | D-lite : Distributed logic for internet of things services[END_REF], a very small virtual machine that gives access to the programming, sensing and actuating abilities of Objects. The Contiki-OS [START_REF] Dunkels | Contiki-a lightweight and flexible operating system for tiny networked sensors. local computer networks[END_REF] version of D-LITe fits in the 48KB Figure 3. In order to build IoT applications, the proposed architectures often use some or all these common software components, under various organization.

of a TelosB5 (with 6LowPAN [START_REF] Kushalnagar | Rfc 4919: Ipv6 over low-power wireless personal area networks (6lowpans): overview. Assumptions, Problem Statement, and Goals[END_REF] and CoAP [START_REF] Shelby | Constrained application protocol (coap). An online version is[END_REF]). This OaaS is accessible through CoAP, and the logic to be run is described with a language called SALT [START_REF] Cherrier | SALT: a simple application logic description using transducers for internet of things[END_REF]. D-LITe is provided for Android too, and there is a Java version for more powerful Objects. So a user can program dynamically, through the network, a new specific service to be executed on his Objects. He can then make them communicate through CoAP, starting a new genuine services interaction, with less dependence on the characteristics of each real Object.

Consequently this distributed intelligence, focusing on local information processing, reduces network load (and avoid to stress networks, some of which are unreliable). This programming service is the main feature of the "Objectas-a-service", and could ensure the success of IoT.

III. SOFTWARE COMPONENTS

IoT applications, by using sensed data or acting on the real world, imply a software architecture designed in order to request, find, and access Objects that provide them. The OaaS paradigm alters this organisation by pushing the "intelligence" into end-devices. Generic IoT application components (the different elements that compose them, and their roles) have already been described [START_REF] Arkko | Architectural considerations in smart object networking[END_REF] [28] [START_REF] Guinard | Interacting with the soa-based internet of things: Discovery, query, selection, and on-demand provisioning of web services[END_REF]. In that section, we propose to categorize different IoT architecture designs regarding their usages of these common software elements (Figure 3), including OaaS.

A. Composition Engine

The composition engine is the visible part of the whole architecture. Its role is to help the user to express his combination of actions, and to describe how the different elements must interact all together. When the architecture in based on a centralized organization, the Workflow remains under the control of that central point of the infrastructure. In such organizations, the central control point follows the Workflow defined by the user, collects data from Objects (or their representation) or triggers actions on them, computes results and organizes the whole application. In a distributed organization, the logic is spread over different stakeholders, and there is no central control. The composition engine is still present at the conception time, to help the user to describe his logic and the Objects interconnections. But here, each object is in charge of its own activity and its behaviour.

B. Discovery and directory

The identification of different objects is crucial to obtain the most relevant informations to answer the user's needs. This identification assumes to be both able to retrieve the access to the object that provides data (or actions), but also to manage the data type that the object sensed (or the type of actions it can trigger) and how to invoke that access. The directory needs relate to both the container and contents. It can be considered as furnishing the same service that a DNS can offer, added with more semantic results, such as Web search engines.

However, we can observe differences in indexing the Internet of Data and the IoT. On one side, the number of accessible objects is already much higher than the number of Internet machines managed by DNS servers. On the other side, Objects contents are much less complex than those hosted by web servers for example (in terms of size, variety and complexity). Indeed, each object provides a rather small amount of data compared to the quantity of pages stored on a web server. However, the limited numbers of different data (or actions) provided by objects can take varied presentations, and therefore their format must be detailed.

C. Drivers repository

IoT deals with a wide diversity of hardware, and the sensing capabilities offered by a sensor (and actions triggered by actuators) are also very varied. Some proposed architectures contain a repository of drivers that give access to all functionalities once the Object is discovered and its type identified. If the driver is available in the repository, the central system can build the application using this object functionalities. The drivers repository gives an high dynamicity to the architecture, because it is a central answer to the stakeholders heterogeneity. As soon as a driver is available, all Objects of this type can be involved in any application.

D. Object virtualisation/Middleware

In most of IoT proposed architectures, the Workflow is centralized (See composition engine above). IoT applications created with these architectures are often under the control of a central point. This central control point is in charge of the execution of the overall application logic. Following this logic, the central control point recovers data gathered by sensors or triggers actions offered by actuators. Access to Objects are often seen through a representation of their instance. This allows to limit interactions with the real Object to a simple data flow, while the central application uses its representation. This offers also a way to bind Objects dynamically, and to change that link if needed. This can also be used to represent a unified data, collected from different sources. For example, the notion of temperature or of movement, in a given area, can be gathered from several Objects. An application may consider that if any movement detector wakes up, the whole zone is to be checked. In the same manner, the temperature can be the average of all measures provided by the sensors over a given perimeter. These data are provided by a representation of the Object(s).

Accessing the representation of an Object can be done through two different ways: a virtualization of the Object, or through a middleware. The main difference between the two solution is their impacts inside the application code. While a virtualization hides totally the fact that it is not the real object that runs the code, the middleware is more invasive. Calls to the middleware specifically appear in the program. By providing a complete replica of the real object, the virtualization hides its presence and is agnostic to the program that uses it. Having a virtual Object, or a representation, provides a good (even if not transparent) access to it and may improve the energy efficiency of the solution [START_REF] Datta | An iot gateway centric architecture to provide novel m2m services[END_REF].

IV. ARCHITECTURES

Because the Oaas paradigm alters the programming pointof-view by providing dynamicity directly on Objects, we propose a classification of the different IoT architectures in order to see the impact of that organization. This classification allows us to compare the different ways Objects are represented in IoT architectures, how applications interact with them, and those that offer a real programming service in Objects (corresponding to our "Object-as-a-Service" definition).

A. Architecture layers

Our classification (Figure 4) references 3 different software layers and 3 different hardware that interact in IoT architectures:

• Software layers are WorkFlow, Virtualization/Middleware and Sensing/Actuating (the latter is the specificity of the IoT).

• Hardware encountered in IoT architectures are Central Control Point, Gateways or Proxy and Objects themselves. The Worflow is in charge of the application logic, at the higher software layer. It drives the whole behaviour and combines services calls and accesses to the Objects. The Workflow describes the user's needs and can make decisions depending on Objects responses, reactivity or failures. The Workflow triggers actions (through actuators) as the result of its analysis of sensed data gathered from other Objects. This Workflow invokes functionalities offered by Objects through the Virtualization/Middleware layer. The Virtualization/Middleware layer represents the real Objects (mostly a representation of this Object) and has the ability to conduct actions or retrieve data. As seen before, it can be accessible via a Middleware (through the addition of some specific instructions in the software or through a virtualization. Finally, Sensing/Actuating is really executed on Objects, which is the measure (in the case of sensors) or the actions (in the case of actuators). This is done at the lower level of our software layers.

Regarding the hardware, we consider at first the Central Control Point. The Central Control Point runs some (or all, depending on the organization) parts described in the previous Section: Service discovery, Driver repository, Composition engine, etc. It can be a real computer (in home automation, or Smart Cities), but is more and more often virtualized in the Cloud. Gateways or Proxy interconnect the local network to the Internet, for example 802.15.4 networks. Their processing capabilities can be used to do some computation on data. Finally, Objects are in charge of sensing or actuating the real world.

B. Architectures classification

When comparing the different architectures that are described in the literature, a classification of their design can be proposed, based on the distribution of software components in relation to the unit responsible for its implementation. The different functionalities (Workflow, Virtualization/middleware) described above are executed on different hardware following the architecture organization proposed by the authors [START_REF] Sarkar | A scalable distributed architecture towards unifying iot applications[END_REF].

In Cloud oriented architectures, most of the functionalities are executed on a central server hosted by a provider. Even the access to Objects, by the meaning of a hardware virtualization, is done in the Cloud. This design is described in the first column ("In the Cloud") of our classification Figure 4. These Cloud-oriented architectures offer an integrated installation and deployment that fit the user need of simplicity. But the distance between the virtualization and the real Objects may have an impact in term of networks load, especially because of the number of connected objects involved. This network loads could be an issue for the constrained and unreliable networks IoT applications require (see for example IoT-6 european project [START_REF] Thomas | Making it all work together enabling new business models in the web of everything[END_REF] [33], Future Internet FI-Ware [START_REF]Fi-ware internet of things(iot) service enablement[END_REF] [30], i-Core [START_REF] Foteinos | A cognitive management framework for empowering the internet of things[END_REF] or Actinium [START_REF] Kovatsch | Moving application logic from the firmware to the cloud: Towards the thin server architecture for the internet of things[END_REF]).

Taking into account the specificities of common Objects Networks used in the IoT (802.15.4 for example), the Middleware/Virtualization part of the solution can be executed closer to the Objects, for example in a router, or in the Internet Box. This Proxy approach offers the possibility to use different kind of protocols, different messages sizes, with a more or less complex auto-description, adapted to the throughput and bandwidth of the networks used. For example, rich describing SOAP messages (on the Internet side) are translated on the other side (the WSAN) into small CoAP exchanges, tailored for 6LowPAN networks. Depending on the computing capabilities of this Proxy, the data processing can be more or less important, lightening the workload of the various stakeholders. This design is called "Assisted-Cloud" or "3 Tiers" in our classification Figure 4. This approach can be found in S.K.Datta et al. [START_REF] Datta | An iot gateway centric architecture to provide novel m2m services[END_REF] or WuKong project [START_REF] Lin | Building smart m2m applications using the wukong profile framework[END_REF].

And finally, the Fully distributed solution (last column of Figure 4) is based on our Object-as-a-Service approach. If a specific service can be defined on each Object, dynamically, on-the-fly, it is possible to compose an IoT application in the manner as a program is build in a procedural programming language (such as the C language). This Fully distributed organization relieves the network of transmitting data as some computation can be directly done on the Object itself. The Object computes data, takes decisions on acting or invokes directly a service on another Object. Then, in cascade, Objects interact depending on their sensing capabilities or orders received from others Objects (see D-LITe [START_REF] Cherrier | D-lite : Distributed logic for internet of things services[END_REF] for example). Even if the lack of central point of control may lead to issues [START_REF] Barros | Service interaction patterns[END_REF], the SOC [START_REF] Peltz | Web services orchestration and choreography[END_REF] [5] [START_REF] Jing | Conformance validation between choreography and orchestration[END_REF] and the IoT [27] [7] community literature propose solutions to solve these problems.

V. CONCLUSION

While the IoT becomes a major subject of interest in both the academy and the industry, a solid foundation still lacks for its development in our everyday life. The Service approach, borrowed from the Service Oriented Computing, lightens the difficulty of developing applications, and offers a solution to compose loosely coupled pieces of software, hardware independent, and interoperable.

In this paper, we advocate for an IoT specific view of the Service approach. We believe that a "services creation" service gives a real advantage for the IoT. It offers the ability to remotely program Objects, dynamically, in order to use their computing capabilities to distribute the logic directly on each of them. Then, Objects implied in the application directly invoke other Objects services, or only send the result of their logical computation, giving a richer information and reducing the network load.

Our "Object-as-a-Service" approach pleads for a rich and universal expressibility of the logic to be executed on each Object. Composing services (their results and their actions) helps to build fully distributed applications, in which each element is autonomous and responsible for its actions and measures, and also interacting with other stakeholders.

In this paper, we also propose a classification of the different IoT software architectures. This classification is based on the organization of the different components that are commonly found in such solutions. This classification describes the various IoT applications designs, how the different parts of the architecture are spread over the stakeholders, and includes our "Object-as-a-Service" approach.

Figure 1 .

 1 Figure 1.The "Object-as-a-Service" architecture. A service (at the bottom of this figure) runs on the Object, using its functionalities (sensing, actuating, computing). This specific service is dynamically created and tailored for user's need, on-the-fly, following the description given by the user on the programming layer (the top service of the figure) offered by this Object.

Figure 4 .

 4 Figure 4. Our architectures classification for Internet of Things applications, according to the software components organization.

such as Tomcat, JonAs, JBoss, WebSphere...

Ericsson white pages (2012) http://www.ericsson.com/res/docs/ whitepapers/wp-50-billions.pdf

as described by M. Weiser

in opposition to the notion of "Internet of Things"

A wireless sensor for research/experimentation http://www.memsic.com


Anthony Lethuillier
email: anthony.lethuillier@latmos.ipsl.fr

Alice Le Gall

Michel Hamelin

Valérie Ciarletti

Sylvain Caujolle-Bert

W Schmidt

G Grard

R Grard

Measuring the permittivity of the surface of the Churyumov-Gerasimenko nucleus: the PP-SESAME experiment on board the Philae/ROSETTA lander

Introduction

The ROSETTA probe will reach later this year its target : the comet Churyumov-Gerasimenko. Among the instruments on board the lander, Philae, the Permittivity Probe experiment, which is part of the SESAME package (Surface Electric Sounding and Acoustic Monitoring Experiment [START_REF] Seidensticker | SESAME -An Experiment of the Rosetta Lander Philae: Objectives and General Design[END_REF]), will measure the low frequency complex permittivity (i.e. dielectric constant ǫ r and electrical conductivity σ) of the first 2 meters of the subsurface of the cometary nucleus. At frequencies below 10 kHz, the electrical signature of the matter is especially sensitive to the presence of water ice and its temperature behavior. It will thus allow to determine the water ice content in the near-surface and to monitor its diurnal and orbital variations. Doing so, PP-SESAME will provide essential insight on the activity and evolution of the comet nucleus.

Theory of Mutual Impedance Probes

PP-SESAME is a mutual impedance probe. Its principle is based on the quadrupole array technique which uses a set of transmitter to inject a current in the ground, and measure: i) the magnitude of the induced potential difference ∆V between a pair of receiving electrodes, ii) the magnitude of the injected current I and iii) the phase shift between them [START_REF] Grard | A mobile four-electrode array and its application to the electrical survey of planetary grounds at shallow depths[END_REF]. The mutual impedance of the array is the complex ratio ∆V /I and normalizing it by the mutual impedance in vacuum we can deduce both the dielectric constant and the electrical conductivity of the surface down to a depth that is of the order of the distance between the receiving electrodes.

In Practice : Determining the complex permittivity with PP-SESAME

PP-SESAME can use 5 electrodes located on the feet of the Philae lander or mounted with other instruments (see Fig. 1). It operates at very low frequencies, in the range 10 Hz-10 kHz. cial for the calibration of the data that will be acquired on the nucleus surface with different combinations of electrodes. In practice, in order to derive the complex permittivity from PP-SESAME active measurements, the influence of both the electronic circuit of the instrument and the conducting elements in its close environment (Philae body, harpoons, ice screw. . . ) must be accounted for. This can be done using the capacityinfluence matrix method. The received voltage V can be expressed as:

V r = [K] -1 I jω ( 1
)
where K is the capacity-influence matrix which can be decomposed as follows:

K = K elec + K env (2)
K elec can be determined by an accurate characterization of the electronic circuit of PP-SESAME. K env depends on the complex permittivity of the medium (ǫ r and σ) and can be determined by modeling.

Figure 2 shows how the mutual impedance measured on the ground and normalized with respect to vacuum is expected to vary as a function of ǫ r and σ. It also illustrates the difference between the PP-SESAME measurements and the ideal case with four isolated electrodes. Such charts will be used to infer the complex permittivity of the ground from PP-SESAME data.

Figure 2: Charts relating the complex ratio Z/Z0 (to be measured) to the real and imaginary parts of the complex permittivity of the ground for an idealized mutual impedance probe (in grey) and accounting for PP-SESAME environment (in red).

Measurements made with the replica of Philae

In absence of spare model of the PP-SESAME, a replica of the instrument was recently built in LAT-MOS (Laboratoire Atmosphères, Milieux, Observations Spatiales), France. This replica will soon (in May 2014) be tested in the frame of a field campaign in the giant ice cave system of Dachstein, Austria. The Dachstein caves formed 10 million years ago. At that time there were probably completely filled with water. Today, their ground is covered with a thick layer of ice (several meters thick), which temperature is rather constant throughout the year. This measurement campaign is a unique opportunity to test the capacity influence matrix method (described in section 3) in a natural icy environment.

Summary and Conclusions

In this paper, we present the work done to prepare the scientific return of the PP-SESAME experiment on board the Philae Lander of the ROSETTA mission. In particular, we have developed a method to correct the measurements from the contamination of the close environment of the electrodes. Next steps include the geo-electrical characterization of materials relevant to comet nucleus at PP-SESAME frequencies and the analysis of the data which should arrive in November.

Figure 1 :

 1 Figure 1: Modeling of PP-SESAME in operation with COMSOL Multiphysics®

Acknowledgments

This project is supported by the Région Ile-de-France (DIM-ACAV program) and the French Spatial Agency CNES.


Spécification fonctionnelle ;

Questions éthiques conceptuel, d'autre part. De manière communément admise, cela nécessite de modéliser tout d'abord, c'est-à-dire de construire une représentation du réel perc ¸u au moyen de symboles et de règles pertinents, de vérifier ensuite, voire de valider dans l'absolu cette représentation, ce modèle, de manière à l'améliorer ou à pouvoir l'utiliser. L'importance de cette modélisation et l'analyse rigoureuse des besoins des systèmes de télémédecine sont encore plus évidents depuis la reconnaissance des projets prioritaires dont la représentation générique se décline en deux méta-modèles : le premier porte sur les activités de téléconsultation, téléexpertise et téléassistance ; le second concerne la télésurveillance.

Introduction

From the perspective of systems engineering, the health program is complex. Its operation is the result of multiple equilibriums arising from interactions between many elements and processes. It is itself interacting with all levels of modern society, e.g. an economic or legal point of view, but also with all sources of health risk issues associated with medical practices and the development of the regulatory and institutional context in Europe. Acting on the health system means changing balances or seeking new ones. Introducing telemedicine is making new interactions possible between patients and caregivers, creating new interfaces.

There is room to improve the healthcare system for patient management, although any changes here must not affect the existing balances between the system components. In other words, all telemedicine policies should aim to reduce territorial disparities and at least preserve existing balances or create news ones within the healthcare system.

Systemics and complexity

For decades, a concept has emerged that can help to solve complex problems in various fields by strong abstraction mechanisms and a number of interesting concepts of generic representation. The systemic approach has complemented if not replaced in some areas the traditional Cartesian approach that has shown its limits.

The system definition adopted in this manuscript is that given by [START_REF] Gallou | Systémique : théorie & applications[END_REF]: ''A system is a set forming a coherent and autonomous unit of real or conceptual objects (hardware, people, actions. . .) organized around a goal (or a set of goals, objectives, aims, projects. . .) by means of a set of relationships (mutual interactions, dynamic interactions. . .), all immersed in an environment''.

A common characterization of the systems is to distinguish those that are complicated from complex ones. A complicated system cannot be understood at first by a person who considers it in his analysis. However, a minimum of information, time and Cartesian approach effectively allows understanding and control of it. For example, a machine that uses the wind to drive pumps, remote control or some intelligent processors can be complicated to use. On the contrary, a complex system [START_REF] Rosnay | Le macroscope -Vers une vision globale[END_REF] cannot be, at any given time, known exhaustively. For example, a healthcare system or even a living organism can never be fully described because it is composed of heterogeneous elements, behaviors and interactions with each other and their environment still unpredictable as they emerge from this contextual organization of the system. This means that a large part of the requirements and knowledge of the system escapes the one who believes. Systemics presents itself as the most excellent way to address the complexity, since it helps to organize the methodology for dealing with a largely unknown system from a person who considers it. Systemic concepts break down traditional disciplinary barriers and provide design research to be relevant to policy-making in complex environments.

Systemics and totality principle

The systemic approach [START_REF] Moigne | La théorie du système général : théorie de la modélisation[END_REF] is to apply this system concept definition and the resolution of the problems posed by it. For this purpose, this approach seeks to link together instead of isolating as a Cartesian approach would, it is therefore based on the overall perception rather than a detailed analysis, considering the interactions rather than the elements and emphasizing the study of transactions taking place at the interface points between the system and the environment. Finally, it provides a focus on the dynamic and interactive aspects that sets up the vision reality. The totality principle therefore occupies a place in systems thinking. It states that a system cannot be reducible to its parts. Concretely, this means that it is essential to know the system requirements to consider the relationships linking its elements. Based on this principle, there are summative and constituent system requirements. Summative requirements of a system are the sum of the requirements of the different elements that constitute it. The component requirements include summative but also those resulting relationships linking the elements requirements. The difference between summative and constituent requirements of a system is what is sometimes called the concept of emergence or the ''system effect''. This concept is often found as a key study and progress in many fields (biology research, service engineering, psychology, artificial intelligence, etc.). In particular, its application to a complex system of services shows patterns of organizations that emerge from all these interactions between system components. These emerging organizations then allow the system to behave with a very effective and consistent ability to adapt and produce innovative solutions.

In the next section, we present a system that provides the basis for our study of telemedicine.

Telemedicine: a complex domain

Definition of telemedicine activities

According to the French regulatory documents (decree-Law n o 2010-1229 of 19 October 2010), telemedicine is a remote medical practice which utilizes advanced telecommunications and information technologies for the delivery of healthcare and the exchange of health information across distances, including the following medical activities (Fig. 1):

• teleconsultation, a procedure whereby medical professionals can consult a patient remotely and interpret the necessary data remotely for medical follow-up; • teleexpertise, whereby a medical professional can seek remotely an opinion of other medical professionals who have the relevant training or skills; • teleassistance, a procedure which enables a medical professional to assist remotely another healthcare professional during the realization of a medical act; • telemonitoring, the ability to monitor and supervise patients remotely.

What conceptual and methodological frameworks to implement to try to capture at least part of the complexity of telemedicine activities? From this point of view, the systemic modeling seemed to be a useful theoretical and conceptual basis for an effort to integrate the notion of complexity, which implies unpredictability and uncertainty. It, therefore, has an important place in our scientific research, especially as we observed that ''modeling is the mainperhaps the first -tool for the study of complex systems'' [START_REF] Simon | Foundations of cognitive science[END_REF].

Characterization of key features of telemedicine domain

In line with the practices of collaborative processes of telemedicine, preparation includes studies, meetings, information activities, publications, management on informatic tools, systems and networks for the exchange and processing of information. Telemedicine activities are effective (in terms of being cost-effective and increasing population reach) medical practices, which are promising for and the organization of healthcare in various medical domains (pediatrics, geriatrics, cardiology, diabetology, etc.) with some and advances in urban and rural healthcare delivery around the world [START_REF] Ekeland | Effectiveness of telemedicine: a systematic review of reviews[END_REF][START_REF] Wallace | A systematic review of the evidence for telemedicine in burn care: with a UK perspective[END_REF][START_REF] Van Den Berg | Telemedicine and telecare for older patients-A systematic review[END_REF][START_REF] Saliba | Telemedicine across borders: a systematic review of factors that hinder or support implementation[END_REF][START_REF] Amorim | Impact of telemedicine implementation in thrombolytic use for acute ischemic stroke: the University of Pittsburgh medical center telestroke network experience[END_REF][START_REF] Mars | Telemedicine and advances in urban and rural healthcare delivery in Africa[END_REF][START_REF] Marcin | Telemedicine in the pediatric intensive care unit[END_REF][START_REF] Benhamou | Telemedicine in the management of diabetic patients: current developments and conditions for success[END_REF][START_REF] Franc | Telemedicine and diabetes: achievements and prospects[END_REF][START_REF]Championing telemedicine adoption and utilization in healthcare organizations in New Zealand[END_REF][START_REF] Adambounou | Plateforme de télémédecine moindre coût pour les pays en développement[END_REF]. There is concern about the appropriateness of methodologies for assessments of telemedicine [START_REF] Ekeland | Methodologies for assessing telemedicine: a systematic review of reviews[END_REF] in general and particularly, the measurement of patient satisfaction with telemedicine [START_REF] Kraai | Heart failure patients monitored with telemedicine: patient satisfaction, a review of the literature[END_REF]. The key factor behind this telemedicine is a correct description in the formulation of the question used to determine the situation's medical background. Other factors affecting the procedure of such telemedicine activities are the purpose, the context and expected results for which the telemedicine is being carried out. The selection of the medical questions examined is determined in the planning stage, and should be strongly influenced by the nature of the telemedicine being requested and by the expected use of the telemedicine results. A preliminary process evaluation reviews telemedicine project and examines project actions to assess whether the results or outcome of the work may be affected by a technological obstacle or barrier.

Therefore, the management of interorganizational and interprofessional collaboration practices is influenced by the context in which it is implemented: the human factors, the issues relating to the procedures and the deployments, the legal framework, the prioritized intervention strategies, and the resources that are mobilized to support the intervention by medical professionals [START_REF] Chopard | Legal, deontological and ethical issues applied to telemedicine. A few insights about telestroke[END_REF].

The first step to take when considering these questions is to determine the background and explanatory information of the planned telemedicine in order to enhance our knowledge and understanding of medical situation and to identify key issues paying particular attention to the associated risks. So, it is fundamental to get a deep understanding of the relationships between telemedicine actors and the organizational controls required to support telemedicine services [START_REF] Lerouge | Telemedicine: technology mediated service relationship, encounter, or something else?[END_REF].

This collected information aims to ensure the proper identification and consistent determination of the following elements associated to any telemedicine activity:

• the purpose of the telemedicine: it is at this stage that the collaborative medical team must analyze the needs and identify the objectives to be set in order to fulfill the requirements of and commitments to the patient. The requesting physician must present the situation and formulate the expertise requested clearly and precisely. He could provide the required physician with the elements they used as a basis to formulate the request contained in their communication. The purpose and impact, as well as the arrangements for the planned use of expertise outcomes may also be specified as conditions of telemedicine; • the nature of the telemedicine: remote medical service involvement depends essentially on the nature of the expertise required and on the conditions of the studied situation. The approach for telemedicine depends on the required physician's expertise, the advice solicitation for diagnosis, treatment or monitoring, the nature of the disease, patient characteristics and patient choice. The subject matter dealt with by telemedicine requires relevant evidence from the contextual medical constraints, case study analysis and key informant analysis to assess and provide meaningful advice or orientation; • the documentation for traceability: a precise formulation of the expected outcomes may be issued for all telemedicine requests for which the resources and the deliverables of an expert medical demand are defined by their inbox and outbox parameters. The produced deliverables must give some indications about its content to the interpretations, findings and recommendations based on the associated professional expertise. The expert report may consists of several elements, containing a written document, sound recording, videotape, file, photograph, chart, graph and information recorded or stored by means of any device. Instructions for an exploitation which meets the requirements for organizational, conceptual or technological interoperability must be given in the documentation supplied with the final report; • the available data: participating experts also examined the availability of data concerning telemedicine and agreed that a knowledgeable analysis helps to point to the most efficient implementation path towards the target medical goals (treatment of cerebral edema in cases of ischemic brain infarct or normalization of blood sugar in cases of diabetes mellitus). Further details and the suitable modalities of remote access to available data enable physicians to collaborate with each other by sharing data sets, expert environments and tools. Each health care service must also lay down specific provisions regarding secure access to its medical data and documents in its information system by means of the communications protocols or internal operating procedures;

• the risks associated with the telemedicine: the engagement of remote expertise requires that the telemedicine management identify and properly manage the principal risks related to their medical procedures. A telemedicine scenario must include the appropriate risk management measures and operational conditions that, when properly fulfilled, ensure that the risks from the practices of the remote expertise are adequately controlled. The challenges faced in designing, installing and operating remote health care systems are multi-faceted e.g. administrative, organizational, technological or medical, either positive or negative. A thorough understanding and consistent application of the criteria for characterization of the risks would be based partially on assessments or judgments that may change due to professional uncertainties and expertise-related hazards; • the requirements or constraints related to the telemedicine: the practice of telemedicine should integrate new standards and regulations and take recent scientific and technical knowledge into account. They are some requirements or constraints which are necessary in order to ensure the security of the telemedicine and the authenticity of the shared documents. Numerous important measures have been taken to guarantee a level of protection of medical data. These measures include the preparation of technical standards or rules.

The management also contains requirements regarding practices and the competencies of the concerned healthcare professionals that the type of telemedicine must provide to potential patients. The telemedicine may be individual, plural, or collective, but in all cases it must be proportionate in order to achieve the target objectives.

Modeling Definition

In the scientific community, the concept of modeling was initially defined by mathematics, such as the construction of an abstract description interpretable but whose goal is to better represent reality. Significantly restrictive definition of which we prefer a much more constructive sense of Jean Louis Le Moigne defines modeling as follows:

''An action of development and intentional construction by composing symbols with models that make sense of a complex phenomenon seen, and amplify the reasoning of the actor throwing a deliberate action within the phenomenon, including reasoning to anticipate the consequences of these actions possible projects'' [START_REF] Moigne | La modélisation des systèmes complexes[END_REF].

We can thus look through modeling to describe, understand, summarize and explain a system considered, in order to better decide or analyze its behavior in response to different determinants, but also to find the information needed to make changes and extensions. Significantly, the systemic modeling with its tools (mapping, analogy, etc.) provides a fruitful reading grid to understand complex situations for analyzing properties and action levers are required for the continuous improvement.

''Model or theory, we all know, however, that we still are facing both old and familiar problems: on the one hand do we have some good methods to find or build, and the other hand to validate or legitimize them?'' [START_REF] Moigne | La modélisation des systèmes complexes[END_REF].

The target scope is the modeling of telemedicine activities, but it seems clear that the concepts developed in this paper can be varied in many ways in other application fields.

The process of systemic modeling

Daniel Durand describes the process of systemic modeling into four modules [START_REF] Durand | La systémique[END_REF]:

• the first module is to define the field of modeling and it has two components. The first element is to establish the purpose of the model, which may be limited to get a good understanding of a system or phenomenon. If this goal can be specified during the modeling process, it is different from the second element: the boundaries. These must be defined from the outset to locate the exchanges between the internal components of the system and its environment; • the second module consists of the design of the model. This is being fulfilled, since the identification of significant elements that will compose the model, including the precision of their characteristics (inputs, outputs, specific relations), through the research of their arrangement and the establishment of their connections; • the third module of the modeling process is to check the behavior of the model, that is to say, to identify invariants and variables, and constraints related to the application of the model to clarify the operation of the system and its dynamic evolution; • the fourth and final module is finally developing scenarios for the application of the model in fields related to the studied system and implement means of validation for qualitative or quantitative development.

Daniel Durand also relies on four precepts defined in [START_REF] Moigne | La théorie du système général : théorie de la modélisation[END_REF] and which are based on systemic modeling: the relevance of which is defined in relation to the modeler; globalism which considers the studied system as a part included in a larger whole, teleology, which is to analyze the model in terms of its purpose and finally agregativity used to connect the components of the model, all of which is a simplification of reality. Similarly, any modeling approach being in the context of systems theory must take into account the systemic expert knowledge. This especially as systems theory provides an informal generic knowledge highlighting the aspects common to several models. This generic knowledge defines, for example, the concepts of flow and nature of flow and processes elementary transformations [START_REF] Rollié | Designing biological systems: systems engineering meets synthetic biology[END_REF]. This knowledge has been reused in work in different areas (e.g. physical and information systems) but with a common goal to help the modeler in a process of systemic modeling by using common concept of flows (Must-Do, Want-to Do, Know-How and Can-Do) proposed by [START_REF] Rosnay | Le macroscope -Vers une vision globale[END_REF].

Different modeling views

Just as a photograph of an object takes different aspects depending on the angle of view, the complex system can be Functional Aspect (What the system is doing)

Structural Aspect

(What constitutes the system)

Behavioral Aspect (Where the system comes from and where it goes) Knowledge Enrichment S Figure 2. The systemic triangulation [START_REF] Moigne | La théorie du système général : théorie de la modélisation[END_REF]. La triangulation systémique [START_REF] Moigne | La théorie du système général : théorie de la modélisation[END_REF]. defined differently depending on the observed appearance. Systemic triangulation [START_REF] Moigne | La théorie du système général : théorie de la modélisation[END_REF] (Fig. 2) observed the system in three different but complementary aspects, each associated with a particular aspect:

• the functional aspect is especially sensitive to the purpose or purposes of the system. We spontaneously seek to answer the following questions in a transparent manner: What is the system in its environment? What is it? • the structural aspect is to describe the system structure, the arrangement of its various components. The focus is much more on the relationship between components than on the components themselves, on the structure more than on the element; • the behavioral aspect (historical or genetic) is related to the evolutionary nature of the system which has a memory and a project capable of self-organization. Only the history of the system will often reflect aspects of its operation.

Naturally, systemic triangulation grows by combining these three approaches. More precisely, it moves from one side to another in a spiral process which allows, at each passage, to gain a better understanding, but without that we cannot believe that we have exhausted this understanding. The previous three aspects, we often add the informational component to describe the data used and generated by the systems. These data (which can be interconnected) need to be understood, manipulated and managed. Meticulous decisions must be made to determine the nature of information that the system can represent and make that information carried by the system can match the real phenomena that we are trying to represent. In practice, taking into account the various aspects simplifies the management of complexity, facilitating human understanding and communication.

Generic functional models for French telemedicine

In the French national context, different medical use cases associated with five priority projects that can be summarized in two generic functional models [START_REF] Barge | National Telemedicine Steering Committee[END_REF]:

• a first generic model (Fig. 3) covers cases of teleconsultation, teleexpertise and teleassistance with the priority projects of ''Permanence of care in medical imaging'', ''Management of care for stroke'', ''Health of detainees'' and ''Care in medical-social structures or home hospitalization''; • a second generic model (Fig. 4) is devoted to the cases of telemonitoring, which mainly correspond to the priority project of ''Management of Chronic Diseases'' (teledialysis, telemonitoring of diabetes, telemonitoring of heart failure, telemonitoring of chronic respiratory failure, follow-up of chronic wounds. . .).

In addition to the two typical situations previously described, an integrated approach will be adopted to discuss the borderline or problematic cases. For instance, telemonitoring activities can be coupled with a teleconsultation, teleexpertise or teleassistance. In case of actual or perceived life-threatening emergency, a protocol may include the option of calling an emergency service, then the medical professional responsible for telemonitoring, allowing it to provide the additional information and relevant comments to the emergency physician. This collaborative telemedicine helps the health care providers to improve the management of the patient on the satellite site and reporting processes to determine its orientation (teleexpertise).

Within the first generic functional model which covers most of the priority areas with the exception of cases of telemonitoring, the main differences between them depends on the operational context and the considerations of temporality:

• operational context: nature of needs/pathologies concerned and, by extension, the types of actors involved, to contextualize according to the concerned medical domain:

• thus, for emergency situations, the ''request for consultation, expertise or remote assistance'' is performed by an emergency physician (applicant) to a radiologist on duty in the case of the ''permanence of care in medical imaging'', a medical expert of neurovascular unit in the case of a ''stroke management'', • regarding the areas of ''Health of detainees'' or ''Care in medical-social structures or home hospitalization'', it is the qualified health professional (doctor, nurse, counsellor, etc.) in the patient's location (detention centre or a health care facility) who makes this request to a specialist located outside (psychiatrist, dermatologist. . .); • considerations of temporality:

• the areas ''stroke management'' (in its acute phase) and, to a lesser degree, ''Permanence care imaging'' are primarily characterized by the acute care setting, requiring the implementation of acts of teleexpertise in real time (the medical acts are not scheduled, immediate care for people who are affected by the diseases is a key element), • in contrast, a teleconsultation of a remote specialist (projects the ''Health of detainees'' or ''Care in medical-social structures or home hospitalization'') covers mostly primary care, which may be delayed with reference to the moment of the initial request for new medical services (planning the proposed act at a later date), • likewise, certain acts of teleexpertise (multidisciplinary coordination meetings in the cases of strokes) may be delayed when they do not necessarily concern emergency situations. This is especially the case of ''ministrokes'' that are very small hemorrhages in the brain, which appeared not to have triggered any symptoms when they happened, but an indication that they did certainly occur is obviously observable when ordinary brain imaging is done at later times.

Ethical implications of the use of information systems in telemedicine

New information and communication technologies (ICTs) play a key role in ensuring the development of telemedicine applications. ICTs give health professional and medical professional quick access to up-to-date clinical and administrative data. They support collaborative activities in a number of key medical areas, addressing generic situations such as teleconsultation, teleassistance and teleexpertise. These technological evolutions lead to behavioral changes among stakeholders. Today, we must manage the information systems with ethical conditions incorporated in information modeling processes, in accordance with the standards of current medical rules and professional ethical codes. Such codes or rules may take various forms such as health legislation, a code of professional practice or accepted medical ethical principles. Bioethical principles [START_REF]Scientific and Cultural Organization[END_REF] can usefully be applied to telemedicine in particular. The ethical guidelines associated with the practices of telemedicine must be grounded in the four ethical principles of the universal human rights [START_REF] Beauchamp | Principles of biomedical ethics[END_REF]; namely, the Principle of Autonomy, the Principle of Beneficence, the Principle of Non-maleficence, the Principle of Justice (Table 1). The ethical principles only make sense if all four of these elements are taken together and if none of them prejudices any other. Frequently and strongly articulated views of autonomous individuals are considered to permit the advancement of these principles without damaging others in the society. The needs of people must be balanced with the requirements of operations, ensuring the best possible care. Faith in ethical safeguards and the fairness of electronic data processing techniques operate so as to strengthen the confidence in telemedicine [START_REF] Béranger | Réflexion éthique sur la pluridisciplinarité et la confidentialité de l'information en imagerie médicale via les nouvelles technologies de l'information et la communication[END_REF]. The deployment of telemedicine applications would be consistent with international human rights norms and standards if they comply with the described ethical principles [START_REF] Béranger | Les enjeux et les bonnes pratiques éthiques en téléradiologie[END_REF]. Besides, observance of these principles would also be in compliance with the laws in effect in the country or territory.

Conclusion

In the early stages of the development of complex systems, such as telemedicine, process modeling is an element that can contribute significantly to the quality and reliability of activities and services developed. In addition, the resulting documents are regularly consulted and operated, from the development phase of the system to maintenance, through formal verification and validation [START_REF] Kamsu-Foguem | Verifiying a medical protocol via visual modeling: the case of a nosocomial disease[END_REF].

The nature of the questions addressed in telemedicine makes it essential to have a coordinated, multidisciplinary and systemic approach involving the various components needed for appropriate analysis of specific characteristics of telemedicine domain. The challenges include [START_REF] Moeckli | Staff acceptance of a telemedicine intensive care unit program: a qualitative study[END_REF]:

• the difficulty in reconciling the organizational, financial, medical and technical objectives having various methodological frameworks that are managed by different responsibilities (health care professionals, public or private health institutions and agencies); • the prerequisite to take into account not only the practical aspects of collaboration, but also the various risks involved -including cultural, ethical and legal factors and the surrounding context; • the need to consider experience and learning capacity among the actors involved in telemedicine activities; • the importance of placing telemedicine devices consistent with the urbanization of health information systems in a dynamic and ergonomic way.

The importance of this modeling and rigorous analysis of the requirements of telemedicine systems is even more apparent since the recognition of the generic representation declined in two meta-models: the first covers the activities of teleconsultation, teleexpertise and teleassistance; the second concerns telemonitoring.

The applications of telemedicine seem justified and have a promising future, but it is important to prevent or control any impacts of the development of intelligent information systems with computerized processing of medical elements (data, images and sounds) [START_REF] Kamsu-Foguem | User-centered visual analysis using a hybrid reasoning architecture for intensive care units[END_REF]. Indeed, we must be able to manage the undesirable effects of automated reasoning [START_REF] Kamsu-Foguem | Conceptual graphbased knowledge representation for supporting reasoning in African traditional medicine[END_REF][START_REF] Doumbouya | Telemedicine using mobile telecommunication: towards syntactic interoperability in teleexpertise[END_REF][START_REF] Kamsu-Foguem | Conceptual graph operations for formal visual reasoning in the medical domain[END_REF][START_REF] Kamsu-Foguem | Using conceptual graphs for clinical guidelines representation and knowledge visualization[END_REF] and contribute to systemic solutions driven by ontologies [START_REF] Kamsu-Foguem | An ontological view in telemedicine[END_REF] to protect the fundamental principles relating to individual rights, freedom, justice and medical deontology. Indeed, apart from the intrusion of privacy that the doctor would answer, medical confidentiality may be violated by telemedicine, in situations where several non-practitioners are involved, since they would not be bound by medical confidentiality. To be as rigorous as possible, it is always necessary to specify that anyone attending activities of telemedicine shall be bound by medical confidentiality with regard to the information and/or documents to which they have access in the performance of their duties [START_REF] Simon | Le décret franc ¸ais de télémédecine : une garantie pour les médecins[END_REF][START_REF] Simon | L'an III de la télémédecine en France[END_REF][START_REF] Simon | Tribute to Professor Louis Lareng[END_REF][START_REF] Lareng | Telemedicine in Europe[END_REF][START_REF] Lareng | La télémédecine: grandeurs et tristesses[END_REF]

Figure 1 .

 1 Figure 1. Characterisation of telemedicine activities. Caractéristiques des activités de télémédecine.

Figure 3 .

 3 Figure 3. The functional model for teleconsultation, teleassistance and teleexpertise. La modélisation fonctionnelle pour la téléconsultation, téléassistance et téléexpertise.

Figure 4 .

 4 Figure 4. The functional model for telemonitoring. La modélisation fonctionnelle pour le télémonitoring.

Table 1

 1 Bioethical principles for telemedicine.

	Les principes bioéthiques pour la télémédecine.
	Principles	Definitions	Rules
	Autonomy	Respect for	To tell the truth
		individual	about all medical
		rights and free	activities
		choices and	Respect for private
		associated	life
		decisions	Protection of the
		(human	confidentiality of
		dignity and	personal information
		human rights)	and records
			To obtain informed
			consent
	Beneficence	The duty to do	Prevention of
		good to	disease
		individuals and	To get rid of the
		society (social	problem at the
		responsibility	source
		and sharing of	To promote the
		benefit)	existing and future
			well-being of the
			people and
			communities of the
			settlement area
	Non-	The duty not	To consider the
	maleficence	to harm others	possible harm that
		(solidarity and	any intervention
		cooperation)	might do
	Justice	The duty to	To give each person
		treat people	due consideration
		equally and	based
		fairly (with	equally deserving of
		equity). This	the time and
		makes it	attention
		possible to	according to their
		deal with the	needs
		same cases in	by the measure of
		the same way	its endeavor
		(respect for	on the basis of its
		cultural	contribution
		diversity and	on its merits
		pluralism,
		non-
		discrimination
		and non-
		stigmatization)

Disclosure of interest

The author declares that he has no conflicts of interest concerning this article.