-Pascal Taranto is currently PR1C at Aix-Marseille University, director of the Centre Gilles Gaston Granger since 2015 (UMR7304, history of philosophy, epistemology and history of science, 50 members) and specialised in Enlightenment philosophy. Since 2016, he has been developing within the unit an ambitious programme on the digital transition of research and teaching, in collaboration with various partners: AMU, CNRS, AMU Institutes (inCIAM, SoMuM, Origines), schools and thematic networks (Eco-Complex, Equipex IDEE, RTP education, SFERE federation, AMPIRIC), and private or semi-private partners (French and European companies on the H2020 Green Deal SMILE call for proposals, submitted in January 2021, and SATT). Co-leader of axis 5 (SHS) of the PEPR PIA4 MonEnvi (Environmental Monitoring) submitted by Fabien Pascal (U. Montpellier) in December 2021. The 2 most advanced funded programmes out of the 10 in preparation, currently in POC (with DI and patents in progress) are: LABΩ (collaborative research platforms, 270K€ SATT, MITI, inSHS, DARII-Sud) and SMILE with IM2NP (self-calibrating multi- sensor system for citizen monitoring of urban air pollution on a dedicated collaborative platform, with Hassan Aziza: 230K€, Satt-SE, DARII-Sud, MITI, inSHS). ATMO3D is a specific part of SMILE, which will be presented in Innovatives SHS 2022. Hassan Aziza is currently MCF HDR at Aix-Marseille University and head of the memory team of the IM2NP laboratory (UMR CNRS 7334). The memory team, with 11 teacher-researchers (4 PR and 7 MCF) addresses advanced microelectronic systems. Hassen Aziza directs and has directed 10 PhD theses and is (co-)author of 50 scientific journals, 86 international conferences with proceedings and 6 patents. Hassen Aziza contributes and has contributed as scientific leader and co-leader to the following programmes and contracts: ANR-DIPMEM (2013), FUI project (2016), European IPCEI NANO 2022 project (2019), DARII-Sud project (2019), CNRS-MITI (2020) and "Drone Tracking" (2020) with the Digital Directorate (DNUM) of the French Ministry of the Interior At the international level, Hassen Aziza collaborates with Delft University of technology (TU Delft), AUB (American University of Beirut) and LIU (Lebanese International University) in the framework of two co- supervised theses. Hassen Aziza was the organizer of the IEEE DTIS international conference as general chair in 2020 (https:// www. lirmm.fr/DTIS2020/) and program chair of the IEEE DTIS conference in 2021 (https:// www. lirmm.fr/DTIS2021/). In addition, Hassen Aziza is a scientific expert referenced by BPI France and the DGRI (General Directorates for Research and Innovation) for the expertise of files related to the CIR (Research Tax Credit) and JEI (Young Innovative Company). In addition to being based in Aix, the doctoral student will work in Mr Aziza's laboratory, the IM2NP MEM team in St-Jérôme, Marseille 13.
The SMILE project, currently at the end of its POC phase, aims to develop a fleet of self-calibrating connected sensors (technological breakthrough, patent pending) distributed among the population and urban services to map urban pollution in 2D in a real way (by low-cost sensors but made accurate and not by algorithmic simulation) at street level, in real time, with the mapped information made available on a collaborative citizen platform, in order to create an incentive community of citizens/academics/politicians/socio-economic world (breakthrough). ATMO3D is the logical continuation of SMILE. The aim is to develop 3D mapping of urban pollutants over the entire relevant atmospheric layer (building height, urban topology, etc.) using drones equipped with sensors. Initial conclusive experiments have been conducted. - Scientific presentation of the project The civil drone market is growing exponentially. Over the period 2012-2019, French manufacturers and operators have experienced a growth of 900% according to a study by Erdyn. In 2018, 78% of the French civil drone market in value was represented by professional drones, compared to 22% for leisure drones. In this context, the proposed project focuses on remote scientific measurement using sensors embedded in drone-type systems. The targeted sensors are environmental sensors capable of assessing the concentration of regulated air pollutants. The pollutants (O3, NO2, NOx, VOC) will be considered, as their presence in the atmosphere gives a direct indication of the level or type of air pollution. The presence of fine particles (PM10, PM2.5) and ultra fine particles (PM1), which are mainly found in urban areas (road traffic and in particular old diesel engines, individual wood heating, industry, etc.) will also be addressed. Concerning harmful substances, the study will be extended to specific sensors targeting man-made emissions of substances such as mercury, lead and cadmium. The project aims to give an additional dimension to the scientific measurement of atmospheric gases by considering the third dimension (i.e. 3D mapping). The impact of mastering such technology is undeniable. Indeed, the proposed system will lead to a better knowledge of the behaviour of atmospheric pollutants (help in the calibration of propagation models in the different heights of the atmospheric layer with meteorological and urban geography data) beyond its 3D pollutant detection capacity.
- The state of the art
Currently there are very few commercial solutions that articulate Drone/pollution sensor (our Test Drone and its sniffer are the only one we know of). There is no universal interface for measuring environmental data from drones like the one we want to develop. Nor is there a global solution for urban air pollution that articulates a fleet of self-calibrating sensors, a mobile application, a collaborative citizen platform (SMILE) and drones equipped with a universal drone/sensor interface (ATMO3D). As far as environmental data measurement itself is concerned, fixed sensors are accurate, but bulky, expensive and energy-consuming. They use classical analysis technologies in physical chemistry, chemiluminescence, gas chromatography, mass spectrometry etc. and are generally calibrated in the laboratory. There are too few of them to cover the territory effectively. There are only 70 measuring stations in the PACA region. The scientific data are therefore not produced with sufficient resolution. Alongside these fixed sensors, mobile sensors are semi-conductor-based sensors, which are easy to handle and take up very little space. However, they do not give the same value for the same concentration measured every few days. This drift is an intrinsic physical characteristic of the technology. The operating principle is based on the variation in conductivity of a semiconductor layer in the presence of a gas. Desorption of the gas is never complete, varies with the sensor and is not very reproducible. To achieve maximum reliability and accuracy, calibration is necessary. This can be done in the laboratory by removing the sensors from the device on a regular basis. However, this approach is very costly at the scale of a distributed sensor network. In this context, the proposed project aims, on the one hand, to set up a system for measuring atmospheric pollutants from drones and, on the other hand, to set up a system for the dynamic self-calibration of mobile sensors (often described as "low-cost") from drones. Very low-cost, scalable and diversified sensors (different gases and particles) can then be deployed on a large scale (2D/3D urban grid) with a satisfactory accuracy to provide data of scientific value.
The consortium for this project brings together designers of electronic sensors, designers of drones and on-board instrumentation, and users of these new means of investigating the spatial variability of environmental data. The main scientific and technical challenges will be related to the autonomy of the UAV and the ability of any measurement system (sensor) to interface with the UAV (universal interface). On the one hand, UAVs are battery-powered and the latter are not designed to power additional sensors. Consequently, the design phase of the sensors will have to find the right balance between functionality, cost, size, weight and consumption. On the other hand, the diversity of UAVs on the market will imply software and hardware modifications at the UAV level in order to propose a universal UAV-sensor interface. The feasibility of the project will be guaranteed since it will rely on the complementary expertise of three partners: the CGGG Centre (social transition and digital uses), the IM2NP (microelectronic sensor technology) and the Flying Eye company specialising in drone technology: https: // www. flyingeye.fr/
Pascal Taranto and the CGGG are carrying out several digital projects that aim to encapsulate raw technologies (microelectronics, AI, algorithms) in digital interfaces designed to encourage the re-appropriation of technology and digital tools by citizens (open and participative science). This philosophy is essentially interdisciplinary because it calls on units seeking disruptive innovations on the one hand, and on the other hand, a social orientation of disruptions thanks to the power of networks and innovations in ergonomics, functionalities, and coherence of platforms. Collaborativity must encourage citizens to commit to changes in awareness and behavioural habits through traditional actions (provision of information, mapping, etc.) but also through the exchange and co-development of solutions with other citizens, public authorities, academic research and the socio-economic world. Environmental pollution, particularly atmospheric pollution, is the indicator that reveals how and to what extent our social organisation of the production of goods, wealth and services is the direct cause, on an individual scale, of deleterious health effects, and on a global scale, of catastrophic environmental effects (global warming directly linked to CO2 production). A coherent and well thought-out monitoring system should have a feedback effect on all stakeholders and help to commit to the climate transition. However, the data provided must be accessible, reliable and accurate. Hassan Aziza is working on the technologies likely to provide such data with the development of a dynamic self-calibration process for environmental sensors designed to compensate for their drift. This process is currently the subject of a patent application with SATT Sud-Est. Since 2018, Pascal Taranto and Hassen AZIZA have been working in close collaboration within the framework of the SMILE project dedicated to the measurement and analysis of atmospheric pollutants, with the aim of maximising the social impact of these measures. (Region DARII project and SATT funding in 2019, submission of an H2020 Green Deal aap, participation in the submission of a PIA4 PEPR - in progress).
- Objectives and deliverables of the ATMO3D project
This project requires the development of a universal sensor-drone interface for 3D mapping of air pollutants and harmful substances, for which we request a reinforcement of our HR capacities (PhD contract). SMILE is a participatory science project (crowdsourcing of air pollution data made available on collaborative 2D mapping platforms). ATMO3D is an evolution of this project. The objective of the PhD student's work will be to develop a software/hardware interface allowing any environmental sensor to be interfaced with a drone in order to obtain 3D maps. One application of these sensor-equipped drones will be privileged: the dynamic self-calibration of "low-cost" sensors embedded in the drone. Indeed, the drone will be used in such a way as to allow dynamic self-calibration of a fleet of "low-cost" environmental sensors, on demand. The calibration process will be as follows: - Based on the type of sensors embedded in the connected object, the drone will target one or more reference stations. - The drone will fly to these stations automatically. - When the drone is co-located with these stations (GPS), the self- calibration of the embedded sensor is performed. - The drone is sent to the connected objects to be recalibrated. - Finally, when the drone is co-located by the connected objects to be calibrated, the sensors automatically calibrate themselves from its data. - An advantage of this technique is that the sensors remain within the connected objects and no re-calibration operation in a laboratory is necessary, as this re-calibration is very expensive if all the sensors of a mobile fleet have to be recovered.
With a fleet of a few hundred inexpensive sensors distributed to citizens (cost of the current prototype produced for the SMILE POC: 90 USD), it is possible to dynamically network a city (mobile sensors distributed to citizens via environmental associations) and to re-calibrate them by drone as soon as the measurement drifts, in order to constantly have reliable data comparable to that of fixed 50K€ stations, on a street scale, in 2D and 3D. Our process, in fine, can make it possible to determine a true signature of the atmospheric pollution of a city at a very fine scale of pollutants and spatio-temporal localization of their production or dispersion, on the whole atmospheric layer, and to compare it with other urban sets on our collaborative platforms. This will make it possible to cross-reflect on the causes and the most satisfactory solutions for all the players in each case. The person recruited must have a strong sensitivity to the SHS issues of citizen empowerment via data collection and be able to lead a real reflection on the impacts of technology on human societies, both in its negative (linked to a certain economic organisation) and positive (for example in a Schumpeterian perspective) aspects. In summary: - universal interface and patentable re-calibration process - Captured data and shared 2D/3D mapping of study sites. - Dissemination of know-how and technology to the scientific community. - Management of the website for sharing experiences in 3D ergonomics. - Reflection on the impact of participatory science on the social representations of citizens and their actions.Web site for additional job details
https: // emploi.cnrs.fr/Offres/Doctorant/UMR7304-PASTAR-001/Default.aspxRequired Research Experiences
Engineering: Master Degree or equivalent
Computer science: Master Degree or equivalent
Mathematics: Master Degree or equivalent
FRENCH: BasicContact Information