Sensors and Smart City
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (25 February 2025) | Viewed by 5793
Special Issue Editors
Interests: cloud; IoT; smart cities; embedded systems; cyber-physical systems
Special Issues, Collections and Topics in MDPI journals
Interests: Internet of Things; embedded systems; cyber-physical systems; edge computing; machine learning; deep learning
Interests: Internet of Things; cyber-physical systems; edge computing; machine learning; deep learning
Interests: smart cities; cooperative smart environments; IoT; cyber-physical systems; continuum computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
A Smart City represents an improvement in today’s cities, both functionally and structurally, that strategically utilizes many smart factors, such as information and communications technology (ICT), to increase a city’s sustainable growth and strengthen city functions while ensuring citizens’ quality of life and health. Cities can be viewed as a microcosm of “objects” with which citizens interact daily: street furniture, public buildings, transportation, monuments, public lighting, and much more.
Moreover, continuous monitoring of a city’s status occurs through sensors and processors applied within real-world infrastructure. The Internet of Things (IoT) concept imagines all these objects being “smart”, connected to the Internet, and able to communicate with each other and with the external environment, interacting and sharing data and information. Each object in the IoT can be both a collector and distributor of information regarding mobility, energy consumption, and air pollution, as well as potentially offering cultural and tourist information. As a consequence, cyber and real worlds are strongly linked in a Smart City. New services, including those generated by AI applications, can be deployed when needed, and evaluation mechanisms can be set up to assess the health and success of a Smart City. Similar to the research conducted in smaller and more specialized environments, techniques to exploit the data coming from the sensing systems in a Smart City may be employed to predict and avoid critical situations affecting urban day life, e.g., considering the mobility scenario, we may refer to traffic congestion, or considering citizen security, we may refer to applications able to generate tailored advice for citizens present in the area of critical conditions.
The aim of this Special Issue is to bring together innovative and unpublished developments in areas related to sensors and smart cities, including but not limited to the following:
- computing and sensing infrastructures;
- cost (of node, energy, development, deployment, maintenance);
- communication (security, resilience, low energy);
- adaptability (to environment, energy, faults);
- data processing (on nodes, distributed, aggregation, discovery, big data);
- self-learning (pattern discovery, prediction, auto-configuration);
- deployment (cost, error prevention, localization);
- maintenance (troubleshooting, recurrent costs);
- applications (both new and enjoying new life);
- smart users experience;
- trust and privacy;
- crowdsourcing, crowdsensing, participatory sensing;
- cognition and awareness;
- cyber–physical systems;
- smart tourism;
- deep learning algorithms with applications in Smart Environments;
- innovative autonomous people–environment (urban Smart Environments) interconnection mechanisms.
Both review articles and original research papers on sensors and Smart Cities are welcome.
Prof. Dr. Antonio Puliafito
Dr. Dario Bruneo
Dr. Fabrizio De Vita
Dr. Giuseppe Tricomi
Guest Editors
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Keywords
- Internet of Things
- smart cities application and services
- city and infrastructure monitoring
- cloud and IoT integration
- artificial intelligence
- signal, image, information processing
- sensor-based management system for smart cities
- pattern recognition
- sensor applications for infrastructure safety monitoring
- risk analysis of smart city and infrastructure
- computer vision applications for defect identification and monitoring
- structural damage prognosis
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