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SENSors and Intelligence in BuLt Environment

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An integrated decision support mechanism to improve the sustainability of smart buildings

An EU-funded project integrated intelligent sensing, energy-efficient communications and AI-based data processing for efficient, green future cities.

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How can sensor design, the internet of things (IoT) (signal acquisition, communications, processing) and artificial intelligence (AI), together, enable the built environment in smart cities to deliver on their energy efficiency, well-being and sustainability targets – without compromising the perceived and sensed comfort of occupants? Working alongside 8 countries and 12 academic and industrial consortium partners, and with the support of the Marie Skłodowska-Curie Actions programme, the SENSIBLE project addressed this question. The project developed several innovative technological solutions based on advanced sensing, IoT and AI. SENSIBLE produced novel designs for integrated photonic sensors based on polarisation and wavelength-agnostic nanophotonic beam splitting, cutting down on fabrication imperfections and costs. It demonstrated intelligent data management for green, sustainable buildings via scalable and trustworthy solutions for machine learning-based load disaggregation, by only requiring smart meter measurements and the ability to visualise explanations of AI-based decisions. Moreover, it created guidelines for responsible, transparent and accountable AI, especially for system developers and scientists.

Smart energy as an answer to diverse environmental issues

SENSIBLE’s smart energy work, particularly that related to load disaggregation technologies, can be used to improve energy efficiency and motivate sustainable behaviour. This is achieved by providing information on the energy consumption of individual appliances in a house or building, leveraging on smart meter deployments worldwide. “With ongoing energy crises and calls for energy conservation, a holistic innovation approach that illuminates appliance energy usage and considers comfort and wellbeing through smart chairs and smart lighting can lead to a more efficient energy management and improved quality of life,” explains project coordinator Vladimir Stankovic. The solution can also be used to support load shifting, appliance automation, home safety, and elderly and patient monitoring by identifying the appliances’ status and recognising any departure from the usual daily routines. It was licenced to an energy service company and has been also used in several follow-up industrial projects. SENSIBLE has already begun to make an impact in tackling climate change and environmental challenges. Narrowband IoT applications and devices connected with drones to replace heavy infrastructures can be used in natural or urban areas in the field of environment, disaster management, or the sports industry. SENSIBLE has extended its findings to tackle sustainability in smart agriculture through quantification of energy consumption of machinery to provide a data-driven measure for decision support and planning in the agri-sector. Its ultra-broadband and low-loss integrated photonics designs can be synergically combined with the integration capacity and low-energy consumption of the silicon photonics platform to target salient societal challenges: smart, green and integrated transport and secure, clean and efficient energy. Furthermore, high-resolution miniaturised microspectrometers can be integrated into drones, fixed stations or handheld devices, for supervising energy generation, distribution and residues.

An impactful project for sustainability in the European built environment

SENSIBLE contributed to building capacity in the AI sector in Serbia, which is timely with the establishment of the Institute for Artificial Intelligence Research and Development of Serbia in 2021 by the local government. Beneficiaries in Serbia and Spain secured follow-on local research grants to grow their research to address societal needs at national level. The findings of SENSIBLE also enabled the British beneficiary to impact the research practice for a UK Research Council-funded doctoral school, as well as government policy via the peer-to-peer learning platform Apolitical, by sharing good practices when it comes to responsible data processing.

Keywords

SENSIBLE, smart buildings, smart sensors, sustainability, IoT, AI, data processing, green, transport, energy, lighting

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