Extending the IoT-Stream Model with a Taxonomy for Sensors in Sustainable Smart Cities

Rodrigo Santos (), Gabriel Eggly, Julián Gutierrez and Carlos I. Chesñevar
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Rodrigo Santos: Department of Electrical Engineering and Computers, UNS, ICIC-CONICET-UNS, Bahia Blanca 8000, Argentina
Gabriel Eggly: Department of Electrical Engineering and Computers, UNS/LISSI-CICPBA-UNS, Bahia Blanca 8000, Argentina
Julián Gutierrez: Department of Electrical Engineering and Computers, UNS, ICIC-CONICET-UNS, Bahia Blanca 8000, Argentina
Carlos I. Chesñevar: Department of Computer Science and Engineering, UNS, ICIC-CONICET-UNS, Bahia Blanca 8000, Argentina

Sustainability, 2023, vol. 15, issue 8, 1-21

Abstract: Sustainable cities aim to have a lower environmental impact by reducing their carbon footprints as much as possible. The smart city paradigm based on the Internet of Things (IoT) is the natural approach to achieving this goal. Nevertheless, the proliferation of sensors and IoT technologies, along with the need for annotating real-time data, has promoted the need for light weight ontology-based models for IoT environments, such as IoT-Stream. The IoT-Stream model takes advantage of common knowledge sharing of the semantics while keeping queries and inferences simple. However, sensors in the IoT-Stream model are conceptualized as single entities, exluding further analysis concerning their features (energy consumption, cost, etc.) or application areas. In this article, we present a taxonomy of sensors that expands the original IoT-Stream model by facilitating the mapping of sensors/actuators and services in the context of smart cities in such a way that different applications can share information in a transparent way, avoiding unnecessary duplication of sensors and network infrastructure.

Keywords: smart cities; sustainable cities; Internet of Things (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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