LIGHTweight edge artificial intelligence for Sensing and WIreless communications in connected FacTories – LIGHT-SWIFT

Artificial intelligence (AI) brings without any doubt huge opportunities to optimize efficiency of every industrial application and is a key point of Industry 4.0. The deployment of various sensors in factories, also called Industrial Internet of Things (IIoT) can either help workers in charge of machine maintenance by detecting abnormal behaviours, thus preventing machine breakdown, or help to localize objects or persons in such complex environments. AI algorithms probably represent the best solution to cope with the huge amount of data provided by sensors, but their complexity is also a severe drawback and the processing is mainly centralized.
Energy is crucial for IIoT, since the more sensors are deployed, the more difficult it becomes to ensure sufficient energy, as batteries would need to be recharged more frequently. Moving the processing closest as possible to the sensors would avoid energy hungry transmissions of data. Most of the latter is indeed useless, since AI algorithms need to be fed with descriptors more than raw data. To further enhance energy efficiency of Edge AI, LIGHT-SWIFT aims at proposing a new methodology to reduce the complexity of AI algorithms, paving the way for sustainable smart sensors in Industry 4.0.
This methodology will be applied to sound sensor nodes able to detect unusual situations, either in machine behaviour but also in the general context of the factory. In case of emergency, the system may have to cope with massive amounts of additional data, entailing a crucial need for extremely reliable high data rate transmissions, despite the limited spectrum resources. The methodology of LIGHT-SWIFT project will therefore be applied to the wireless transmissions themselves, to optimize the radio resource access, while achieving the best possible energy efficiency. To reach this goal, our project will leverage a well-balanced consortium composed of two academic partners, IRISA and NII, that work respectively on energy efficient wireless sensor networks and edge AI for wireless communications, the Small and Medium-sized Enterprise (SME) Wavely specialized in sound event detection for IIoT, and one of the largest telecommunications operating companies in the world, NTT, with applications in Industry 4.0.