Identification of Crowds Using Mobile Crowd Sensing (MCS) and Visualization with the DBSCAN Algorithm for a Smart Campus Environment DOI Creative Commons

Luis Chirinos-Apaza

Опубликована: Ноя. 23, 2024

Multidisciplinary research, in conjunction with artificial intelligence (AI), the Internet of Things (IoT), Blockchain and Big Data analysis, has lowered barriers made companies more productive, other words, joint work these areas promoted digital transformation all areas, for example Artificial (AI) it possible to automate processes, (IoT) connected devices physical objects, enabling real-time data collection analysis. provided a secure transparent way transact store data. analysis allowed obtain valuable insights from large amounts As technologies continue evolve, we can expect see even innovations benefits future. This paper explores feasibility using Mobile Crowd Sensing (MCS) visualization algorithms detect crowding on university campus. A survey was conducted evaluate community’s perception mobile application that provides information about crowds, detection scenario simulated randomly generated DBSCAN algorithm visualization. Preliminary results suggest system is viable could be useful tool prevention accidents due management public spaces. The limitations study are discussed future lines research proposed, such as crowd prediction, privacy, optimization.

Язык: Английский

Identification of Crowds Using Mobile Crowd Sensing (MCS) and Visualization with the DBSCAN Algorithm for a Smart Campus Environment DOI Creative Commons

Luis Chirinos-Apaza

Опубликована: Ноя. 23, 2024

Multidisciplinary research, in conjunction with artificial intelligence (AI), the Internet of Things (IoT), Blockchain and Big Data analysis, has lowered barriers made companies more productive, other words, joint work these areas promoted digital transformation all areas, for example Artificial (AI) it possible to automate processes, (IoT) connected devices physical objects, enabling real-time data collection analysis. provided a secure transparent way transact store data. analysis allowed obtain valuable insights from large amounts As technologies continue evolve, we can expect see even innovations benefits future. This paper explores feasibility using Mobile Crowd Sensing (MCS) visualization algorithms detect crowding on university campus. A survey was conducted evaluate community’s perception mobile application that provides information about crowds, detection scenario simulated randomly generated DBSCAN algorithm visualization. Preliminary results suggest system is viable could be useful tool prevention accidents due management public spaces. The limitations study are discussed future lines research proposed, such as crowd prediction, privacy, optimization.

Язык: Английский

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