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PROFESJON-Forskningskompetanse for utvalgte profesjonsutdanninger

Multiparameter Active Antenna Sensor

Alternative title: Antennesensor for aktiv sensing av flere parametere

Awarded: NOK 10.0 mill.

With the expansion of the internet-of-things (IoT) in various sectors, the number of connected devices is expected to reach 75 billion by 2025. One of the main use-cases of such devices is to sense one or more physical parameters for monitoring and/or actuation purposes. The rapid expansion and massive deployment of these devices rise the need for new design consideration to support its future sustainability in terms of hardware use and power consumption. Triggered by this, the project explores the revolutionary secondary use of the sensor node antenna for multiple parameter sensing purposes using sensitive sensing materials deployed on the antenna surface. This eliminates the conventional use of the sensor integrated circuits (ICs) and microcontrollers, and their associated power consumption. The idea is to move the complexity from the sensor node to the computation of the sensor data receiving station, where signal processing and machine learning techniques are employed to remotely sense the considered physical parameters. The sensing is done by detecting changes on the antenna radiation characteristics caused by the applied sensing materials. The idea of using the antenna as an active sensor for sensing multiple parameters is an absolute novelty. If successful, it will reduce the hardware use of a standard sensor node by at least 50% (i.e. no sensor ICs, sampler and processor, and memory will be needed along with their associated power consumption), resulting in more than doubling their battery lifetime. Strategically, the project will strengthen the research-based professional educations and practices within electronics to meet the current and future needs of experts with the new knowledge and the innovation that the project brings. The ambition is to create a new generation of IoT devices that use the antenna not only for radiating electromagnetic waves, but also has a secondary functionality of actively sensing multiple physical parameters.

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With the expansion of the internet-of-things (IoT) in various sectors, the number of connected devices is expected to reach 75 billion by 2025. One of the main use-cases of such devices is to sense one or more physical parameters for monitoring and/or actuation purposes. The rapid expansion and massive deployment of these devices rise the need for new design consideration to support its future sustainability in terms of hardware use and power consumption. Triggered by this, the MAAS project explores the revolutionary secondary use of the sensor node antenna for multiparameter active sensing purposes using sensitive sensing materials deployed on the antenna surface. This eliminates the conventional use of the sensor integrated circuits (ICs) and microcontrollers, and their associated power consumption. The idea is to move the complexity from the sensor node to the computation of the gateway station, where signal processing and machine learning techniques are employed to remotely sense the physical parameters. This is done by detecting changes on the radiation characteristics of the antenna sensor caused by the applied sensing materials. The idea of using the antenna as a multiparameter active sensor is an absolute novelty. If successful, it will reduce the hardware use of a standard sensor node by at least 50% (i.e. no sensor ICs, sampler and processor, and memory will be needed along with their associated power consumption), resulting in more than doubling their battery lifetime. Strategically, the project will strengthen the research-based professional educations and practices within electronics to meet the current and future needs of experts with the new knowledge and the innovation that the project brings. The ambition is to create a new generation of IoT devices that use the antenna not only for radiating electromagnetic waves, but also has a secondary functionality of actively sensing multiple physical parameters (without using sensor ICs and a microprocessor).

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Funding scheme:

PROFESJON-Forskningskompetanse for utvalgte profesjonsutdanninger

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