Smart Spaces: Occupancy Detection using Adaptive Back-Propagation Neural Network

Saleem, Muhammad; Khan, Muhammad Saeed; Issa, Ghassan F.; Khadim, Assma; Asif, Muhammad; Akram, Ali Sheraz; Nair, Harish K G

doi:10.1109/icbats57792.2023.10111286

Cited by 10 publications

(2 citation statements)

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“…Moreover, used in business analytics for technological security, smart architectural spaces and occupancy detection. Therefore, constructing efficient and sustainable buildings that prioritize energy efficiency and comfort [10]. Additionally, Artificial Neural Networks (ANNs) developed as a computational model of the human nervous system [10].…”

Section: A Real-life Scenarios and Real-world Impactmentioning

confidence: 99%

“…Therefore, constructing efficient and sustainable buildings that prioritize energy efficiency and comfort [10]. Additionally, Artificial Neural Networks (ANNs) developed as a computational model of the human nervous system [10]. They simulate the human brain, and these learning algorithms are based on acquired experiences [10.…”

Section: A Real-life Scenarios and Real-world Impactmentioning

confidence: 99%

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Balancing Automation: Evaluating the Impacts of Landborne and Airborne Automation in Industry

Mbelekani

2024

Preprint

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Automation technological innovations have become fundamental in humans’ lives and societal evolution. Thus, it is crucial to consider possible impacts, consequences and benefits as the future sees a greater use of it. Such as long-term effects, for example. Primarily, economic-based effects, where automation is said to create as many jobs as it destroys over time. Furthermore, ergonomic effects and human factors influence users’ behaviour towards automation, for example, trust, utilisation, and receptivity. Evidently, the paper intends to explore these topics, carefully considering vehicle automation-induced effects and automated vehicle (AV). In essence, the views provided in this paper are based on an industry-centred study, with twenty landborne and airborne automation experts. The aim is to constructively open discussions for further empirical assessments, and pursue knowledge on direct and indirect effects. Therefore, extending the knowledge gap beyond the simple replacement of humans by automation, but also the human experience and behaviour towards such systems. Marie Skłodowska-Curie Actions; Innovative Training Network (ITN); SHAPE-IT; Grant number 860410

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Section: A Real-life Scenarios and Real-world Impactmentioning

confidence: 99%

Section: A Real-life Scenarios and Real-world Impactmentioning

confidence: 99%