Rural Environmental Monitoring via ultra wide-ARea networKs And distriButed federated Learning

Lead Research Organisation: Manchester Metropolitan University
Department Name: School of Engineering

Abstract

Internet of Things (IoT) technology combined with complementary support for data analytics is the corner stone of today's digital transformation. The societal and economic impact of IoT/ML systems in urban and suburban areas significantly outpaces the one in rural areas due to a limited reach of connectivity infrastructure. To reverse further widening of the urban-rural gap, we need to bring efficient and affordable IoT/ML solutions to deep rural areas, reaching out to applications and use cases ranging from wildlife management, rural tourism, livestock monitoring, water and air pollution control, and others. By identifying main gaps in connectivity and affordable data analytics and through interleaved research, development and validation in a real-world setting, REMARKABLE will address the challenge of bringing IoT and data analytics systems a step closer to seamless, energy efficient and secure deployment in
rural ares. The consortium composed of six European academic partners, five companies and five associated partners representing leading academic groups from Africa, will focus on research, development, innovation and demonstration across five use cases with six demonstration sites located in rural areas across the European and African continent. The inter-disciplinary nature of the programme provides a unique opportunity for investigation of smart sensing, IoT and data science technology from non-traditional, holistic perspectives leading to new scientific achievements and innovations. Project outputs like smart IoT sensors and devices, rural IoT digital twining platforms, ultra wide-area IoT networks, novel data analytics models and architectures will find their routes to the market via active industrial partners. The project will impact EU workforce market via new interdisciplinary skills for young contributors and form new long-lasting networks of European and African institutions in the area of sensing, IoT, big data analytics and rural entrepreneurship.

Publications

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Popoola S (2023) Federated Deep Learning for Intrusion Detection in Consumer-Centric Internet of Things in IEEE Transactions on Consumer Electronics