Trainee Project
Title:
Hardware and Software Optimization of an IoT System for Industrial Safety Management
Dates:
2025/04/01 - 2025/07/31
Student:
Supervisor(s):
Description:
Context and Challenges
This internship is part of the continuation of the ANR I2RM project (N°ANR-21-SIOM-0007), titled "Interactive and Intelligent Physical Assets
Control System for the Risk Management of Hazardous Industrial Facilities", led by CRAN (Nancy) and LAMIH (Valenciennes). The objective is to
optimize the hardware architecture of an autonomous communicating device, SAMOCA, integrated into an industrial IoT architecture (Device-Edge-
Cloud), designed by CRAN and dedicated to real-time monitoring and risk prevention in sensitive industrial environments.
The developed system aims to enable proactive industrial risk management by identifying and preventing critical interactions between products,
machines, and human operators, thereby reducing the likelihood of major industrial accidents (e.g., Lubrizol plant disaster in Rouen, AZF explosion
in Toulouse). The system is based on an integrated approach combining anticipation, prevention, avoidance, and real-time alerts. It enables detection
and analysis of anomalies related to positioning, movement, and storage of industrial assets, as well as unsafe interactions with other equipment and
human operators [1][2] .
A functional prototype (Proof of Feasibility ⬓ POF), entirely developed at CRAN, has successfully validated the concept in an experimental
environment. However, further optimizations are required to transition towards a pre-industrialization phase.
Internship Objectives
The objective is to optimize the existing hardware solution while incorporating performance, miniaturization, energy autonomy, and cost reduction
constraints to facilitate large-scale deployment. The key optimization areas include:
⬢ Energy Autonomy: Maximizing energy efficiency to achieve two years of autonomous operation.
⬢ Form Factor: Reducing the device size while ensuring structural and functional integrity.
⬢ Advanced Sensing: Integrating additional physico-chemical sensors for multi-parameter monitoring.
⬢ Economic Optimization: Reducing manufacturing costs while maintaining high robustness and reliability standards.
Scope of Work
The optimization process will focus on two complementary aspects:
1. Hardware Optimization
⬢ Selection and qualification of appropriate electronic components (microcontrollers, sensors, power management circuits).
⬢ Design of an optimized hardware architecture: schematic development, PCB routing, and manufacturing file generation.
⬢ Development and implementation of advanced energy management strategies (low-power operation in active and standby modes).
⬢ Prototyping and functional testing in a laboratory environment.
2. Software Optimization
⬢ Porting and adapting existing software to the new hardware architecture.
⬢ Optimization of embedded algorithms to improve energy efficiency and real-time processing.
⬢ Integration of new sensors for enhanced monitoring capabilities.
⬢ Validation and performance testing under representative industrial scenarios.
This internship offers an opportunity to contribute to a high-impact applied research project, focusing on the development of an advanced IoT
solution that combines embedded intelligence, optimized connectivity, and energy resilience for industrial risk management.
[1] TIJJANI A.S., BAJIC E., BERGER T., DEFOORT M, SALLEZ Y., DJEMAI M, RUP C., MEKKI K. "Distributed control architecture for the
risk management of hazardous industrial facilities", SOHOMA22, 12th International Workshop on Service-Oriented, Holonic and Multi-Agent
Manufacturing Systems for Industry of the Future, September 22-23, 2022, Bucharest, Romania {hal-03899484}
[2] C. RUP, BAJIC E., MEKKI K., "Snowball: An Asynchronous Probabilistic Protocol for Neighbour Discovery in Mobile BLE Network," 2022
IEEE 8th World Forum on Internet of Things (WF-IoT), Yokohama, Japan, 2022, pp. 1-8, doi: 10.1109/WF-IoT54382.2022.10152274 {hal-
03823749}
This internship is part of the continuation of the ANR I2RM project (N°ANR-21-SIOM-0007), titled "Interactive and Intelligent Physical Assets
Control System for the Risk Management of Hazardous Industrial Facilities", led by CRAN (Nancy) and LAMIH (Valenciennes). The objective is to
optimize the hardware architecture of an autonomous communicating device, SAMOCA, integrated into an industrial IoT architecture (Device-Edge-
Cloud), designed by CRAN and dedicated to real-time monitoring and risk prevention in sensitive industrial environments.
The developed system aims to enable proactive industrial risk management by identifying and preventing critical interactions between products,
machines, and human operators, thereby reducing the likelihood of major industrial accidents (e.g., Lubrizol plant disaster in Rouen, AZF explosion
in Toulouse). The system is based on an integrated approach combining anticipation, prevention, avoidance, and real-time alerts. It enables detection
and analysis of anomalies related to positioning, movement, and storage of industrial assets, as well as unsafe interactions with other equipment and
human operators [1][2] .
A functional prototype (Proof of Feasibility ⬓ POF), entirely developed at CRAN, has successfully validated the concept in an experimental
environment. However, further optimizations are required to transition towards a pre-industrialization phase.
Internship Objectives
The objective is to optimize the existing hardware solution while incorporating performance, miniaturization, energy autonomy, and cost reduction
constraints to facilitate large-scale deployment. The key optimization areas include:
⬢ Energy Autonomy: Maximizing energy efficiency to achieve two years of autonomous operation.
⬢ Form Factor: Reducing the device size while ensuring structural and functional integrity.
⬢ Advanced Sensing: Integrating additional physico-chemical sensors for multi-parameter monitoring.
⬢ Economic Optimization: Reducing manufacturing costs while maintaining high robustness and reliability standards.
Scope of Work
The optimization process will focus on two complementary aspects:
1. Hardware Optimization
⬢ Selection and qualification of appropriate electronic components (microcontrollers, sensors, power management circuits).
⬢ Design of an optimized hardware architecture: schematic development, PCB routing, and manufacturing file generation.
⬢ Development and implementation of advanced energy management strategies (low-power operation in active and standby modes).
⬢ Prototyping and functional testing in a laboratory environment.
2. Software Optimization
⬢ Porting and adapting existing software to the new hardware architecture.
⬢ Optimization of embedded algorithms to improve energy efficiency and real-time processing.
⬢ Integration of new sensors for enhanced monitoring capabilities.
⬢ Validation and performance testing under representative industrial scenarios.
This internship offers an opportunity to contribute to a high-impact applied research project, focusing on the development of an advanced IoT
solution that combines embedded intelligence, optimized connectivity, and energy resilience for industrial risk management.
[1] TIJJANI A.S., BAJIC E., BERGER T., DEFOORT M, SALLEZ Y., DJEMAI M, RUP C., MEKKI K. "Distributed control architecture for the
risk management of hazardous industrial facilities", SOHOMA22, 12th International Workshop on Service-Oriented, Holonic and Multi-Agent
Manufacturing Systems for Industry of the Future, September 22-23, 2022, Bucharest, Romania {hal-03899484}
[2] C. RUP, BAJIC E., MEKKI K., "Snowball: An Asynchronous Probabilistic Protocol for Neighbour Discovery in Mobile BLE Network," 2022
IEEE 8th World Forum on Internet of Things (WF-IoT), Yokohama, Japan, 2022, pp. 1-8, doi: 10.1109/WF-IoT54382.2022.10152274 {hal-
03823749}
Department(s):
| Modelling and Control of Industrial Systems |
Publications: