A vector-sensor based approach to noise monitoring in Galway Bay
Albert Akhriev, John Sheehan, et al.
OCEANS 2014
Relatively tiny examples have demonstrated the potential of cognitive IoT (CIoT) in its full-stack, namely, semantic modeling, learning and reasoning over sensors data, and machine learning, to uncover and expose actionable insights via advanced user interfaces. In this paper, we make the case for the feasibility of CIoT in all of its dimensions. We devise a CIoT architecture that integrates thousands of sensors present in our buildings in order to learn the buildings’ behavior and intuitively assist users in diagnosing and mitigating undesired events. With our architecture, we place emphasis on the scalability and flexibility that reduce the configuration effort. The solution shows the potential of CIoT to create highly scalable, adaptable and interactive IoT systems functioning for buildings and capable of addressing the challenges encountered in the realm of homes, Smart Cities and Industry 4.0.
Albert Akhriev, John Sheehan, et al.
OCEANS 2014
Joern Ploennigs, Bei Chen, et al.
BuildSys 2013
Joern Ploennigs, Jana Clement, et al.
BuildSys 2015
Bharathan Balaji, Arka Bhattacharya, et al.
Applied Energy