Minor Sensor and Network Devices

The evolution of sensor technology and communication protocols has made it possible to realize connected objects whose application domains are in full expansion.
This teaching unit aims to provide theoretical and practical bases for the development of connected objects by the design of the Cherokey 4WD arduino mobile robot. It is a versatile mobile robot that is compatible with popular microcontrollers such as the arduino UNO, arduino MEGA 2560, Romeo, etc.
In order to address the network aspect, sensor nodes (M5Stack family) will monitor physical data and forward the collected information to a central node (Raspberry Pi) in charge of decision for actuator nodes. The central node will rely on machine learning algorithms (KNN, RF, SVM, CNN, …) for making centralized decisions. The efficiency of different algorithms of ML will be compared.

​This course will be divided into two parts: 

• Robot building and controlling and Bluetooth communication:
  • The first step will be devoted to understanding how the robot works, discovering the Arduino language and its functions.
  • The second step is dedicated to programming the Cherokey Robot and to find the function that will allow the robot to avoid obstacles.
  • The last step will be to use the Bluetooth function and the camera to move the robot.
• Design of sensor network:
  • The first step is to build a sensor network and a data collection infrastructure based on WIFI communication, a broker (MQTT) and nodered.
  • The second step is to integrate machine learning (ML) algorithms for making decisions based on collected data. The different steps of the ML deployment will be studied.

• Jean-Marc Ribero, Professor, Université Côte d'Azur, LEAT laboratory.
  Field of expertise: Antenna Design and Modeling, Miniaturized Multiband and Reconfigurable Antennas, Multi-Antenna Systems (MIMO and Massive MIMO), Integrated Antennas for IoT Devices, Smart Building and e-Health Wireless Technologies.
  5G and Future Wireless Communication Networks
• Cécile Belleudy, Associate professor, Université Côte d’Azur, LEAT laboratory.
  Field of expertise: Embedded Systems and Internet of Things (IoT) Wireless Sensor Networks and Data Acquisition Systems, IoT Communication Protocols (Wi-Fi, Bluetooth, MQTT, etc.), Edge Computing and Distributed Systems, Machine Learning for IoT and Cyber-Physical Systems Smart Environments (Smart Homes and Smart Buildings).

• Basic in programming language

• Akyildiz, I. F., & Vuran, M. C. (2010). Wireless Sensor Networks. John Wiley & Sons.
• Karl, H., & Willig, A. (2005). Protocols and Architectures for Wireless Sensor Networks. John Wiley & Sons.
• Bahga, A., & Madisetti, V. (2014). Internet of Things: A Hands-On Approach. Universities Press.
• Hanes, D., Salgueiro, G., Grossetete, P., Barton, R., & Henry, J. (2017). IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things. Cisco Press.
• Géron, A. (2022). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems (3rd ed.). O'Reilly Media.

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