Offer Description
A critical challenge to deploying the Internet of Things (IoT) and wireless sensor networks (WSN) is the ability to collect and transmit data over the Internet at low energy costs and using sustainable solutions. The maturity of energy harvesting technologies and low-power microcontrollers opens the prospect of developing batteryless computing for WSN and IoT applications.
We thus expect the advent of intermittently-powered, batteryless devices that operate entirely using energy extracted from their environment. Intermittently operating devices present numerous technological challenges in various domains (electronics, IT, etc.). Among the interesting challenges, we can highlight the prediction of the harvested energy, the evaluation of the available energy and the estimation of the consumed energy through very fine consumption models (taking into account in particular the sensor, the microcontroller and data transmission). The architecture and structure of the node is also an important subject in this context of minimizing the consumed energy. Intermittent computing also presents other issues related to data storage (non-volatile memory) and prolonged execution of batteryless computing applications.
In the context of IoT, there are many use cases (smart agriculture, smart city, smart building, industry 4.0, etc.). Each use case is specific in terms of data rate, latency, communication range, frequency of data transmission. It is obvious that the use case will have a significant impact on energy consumption and therefore on energy management and the energy that must be harvested.
The first objective of this work will be to identify the use cases that will be considered. Then the different way allowing energy harvesting will be studied. From this, a predictive energy harvesting model will be proposed as well as an energy consumption model. The second objective will be to set up a testbed. It will allow practical evaluation and the obtained measurement results will feed the models to refine them. The results will also make it possible to improve the energy harvested prediction algorithm. Finally, the links between the sensor, the predictor and the transmitter will make it possible to implement efficient energy management methods that will optimize the operation of the node.
For this study, we will use the devices and the analysis and measurement equipment of the connected objects platform of the IETR lab.
According to provided results, an opening could be made on the network aspect. Taking into account several nodes could lead the study towards distributed optimization and fog computing.
Among the scientific challenges to be addressed, this PhD project will focus on:
• The study and selection of energy harvesting methods;
• The proposal of new prediction and energy consumption models which will be refined through practical experiments;
• The promotion and dissemination of this work via research publications.
Requirements
Skills/Qualifications
Knowledge on design of connected objects, protocols and telecommunications are mandatory.
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STATUS: EXPIRED
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