Blar i NTNU Open på forfatter "Veiga, Tiago Santos"
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Blind Calibration of Air Quality Wireless Sensor Networks Using Deep Neural Networks
Veiga, Tiago Santos; Ljunggren, Erling; Bach, Kerstin; Akselsen, Sigmund (Chapter, 2021)Temporal drift of low-cost sensors is crucial for the applicability of wireless sensor networks (WSN) to measure highly local phenomenon such as air quality. The emergence of wireless sensor networks in locations without ... -
From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development
Veiga, Tiago Santos; Munch-Ellingsen, Arne; Papastergiopoulos, Christoforos; Tzovaras, Dimitrios; Kalamaras, Ilias; Bach, Kerstin; Votis, Konstantinos; Akselsen, Sigmund (Peer reviewed; Journal article, 2021)Air pollution is a widespread problem due to its impact on both humans and the environment. Providing decision makers with artificial intelligence based solutions requires to monitor the ambient air quality accurately and ... -
On the Use of Air Quality Microsensors for Supporting Decision Makers
Bach, Kerstin; Akselsen, Sigmund; Veiga, Tiago Santos; Kalamaras, Ilias (Chapter, 2020)In this poster we present how a network of Internet-of-things (IoT) devices facilitated through machine learning can improve decision making. Our application domain is air quality in the municipality of Trondheim. Ambient ... -
Towards containerized, reuse-oriented AI deployment platforms for cognitive IoT applications
Veiga, Tiago Santos; Asad, Hafiz Areeb; Kræmer, Frank Alexander; Bach, Kerstin (Peer reviewed; Journal article, 2022)IoT applications with their resource-constrained sensor devices can benefit from adjusting their operations to the phenomena they sense and the environments they operate in, leading to the paradigm of self-adaptive, ... -
A Unified Decision-Theoretic Model for Information Gathering and Communication Planning
Renoux, Jennifer; Veiga, Tiago Santos; Lima, Pedro; Spaan, Matthijs (Chapter, 2020)We consider the problem of communication planning for human-machine cooperation in stochastic and partially observable environments. Partially Observable Markov Decision Processes with Information Rewards (POMDPs-IR) form ...