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Ubiwhere is developing technologies for Resource-Efficient IoT-Edge Systems | News - Ubiwhere

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SEP 07 2022

Ubiwhere is developing technologies for Resource-Efficient IoT-Edge Systems

Ubiwhere

Riot-ES (Resource-Efficient IoT Edge Systems) will investigate a mix of sensor devices as well as computational and data management platforms where the complementary expertise of the project partners will create strong synergy and a thorough understanding of IoT edge systems. As one of Ubiwhere’s projects, RIOT-ES has one primordial goal: to unlock a world of opportunities for IoT.

IoT systems consume significant energy, making energy efficiency one of the most important issues. IoT technologies have the potential to transform society, make cities smart, and increase the quality of life through smart home care. Still, IoT is not yet a mature technology prepared to achieve the envisioned innovation.

Riot-ES is a project developed by Ubiwhere and PROEF focused on addressing the main challenges regarding the use of IoT. As Energy efficiency and performance are often at odds with each other, the project’s main goal will be investigating solutions to optimise energy efficiency given performance constraints and, conversely, optimise performance given energy constraints. Riot-ES researches and develops new methods, technologies, and systems for maximising energy efficiency and increased performance in IoT systems, focusing on IoT devices and processing at the edge of wireless networks.

The project will investigate a mix of sensor devices and computational and data management platforms, which will be used in two different use cases: Smart Home and Smart Cities.

In the field of Smart Cities, Ubiwhere and PROEF will explore a realistic urban scenario by leveraging Ubiwhere’s Smart Parking solution by implementing and demonstrating the addition of a video camera to monitor the available slots in a real-time parking facility.

In the envisioned deployment, cameras will be connected to one or more edge nodes and stream the acquired media data in real time. The edge nodes will pre-process the data with lightweight image recognition algorithms. Through this solution, network consumption resources and the computational power needed to fully process all the streams acquired from a smart-parking deployment will decrease by avoiding sending all media data to a cloud central node responsible for fully processing all these streams in real time.

This solution is about to develop new methods, technologies, and systems to maximise energy efficiency and increase performance in IoT systems, with a focus on IoT devices and edge processing of wireless networks and to investigate a combination of devices, sensors and computational and data management platforms, where the complementary expertise of the project partners will create strong synergy effects and understanding of all parts of global IoT edge systems.

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