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Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
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Some compounds produce hydroxide ions when dissolved by chemically reacting with water molecules. In all cases, these compounds react only partially and so are classified as weak bases. These types of compounds are also abundant in nature and important commodities in various technologies. For example, global production of the weak base ammonia is typically well over 100 metric tons annually, being widely used as an agricultural fertilizer, a raw material for chemical synthesis of other...
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An IoT Surveillance System Based on a Decentralised Architecture.

Amilcare Francesco Santamaria1, Pierfrancesco Raimondo2, Mauro Tropea3

  • 1DIMES Department-University of Calabria, via Pietro Bucci cubo 39/c V piano, 87036 Rende (CS), Italy. afsantamaria@dimes.unical.it.

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Summary

This study introduces a decentralized surveillance system using Internet of Things (IoT) protocols and mist computing for faster threat detection in public areas. The approach enhances security through intelligent, distributed analysis and computer vision, ensuring rapid response capabilities.

Keywords:
OpenCVcomputer visiondronesinternet of thingslightweight protocolsmist computingsurveillance

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Security Studies

Background:

  • Rising threats in crowded public spaces necessitate advanced surveillance.
  • Existing systems often lack the speed and scalability for real-time threat detection.

Purpose of the Study:

  • To develop a decentralized surveillance architecture for public spaces.
  • To leverage Internet of Things (IoT) protocols and mist computing for enhanced threat identification.
  • To improve reaction times in detecting potential security menaces.

Main Methods:

  • Implementation of a decentralized architecture for managing patrolling drones and cameras.
  • Utilization of lightweight Internet of Things (IoT) protocols.
  • Application of mist computing to distribute intelligence within the surveillance ecosystem.
  • Employment of computer vision algorithms for object recognition.

Main Results:

  • Demonstrated faster recognition and reaction to potential warning situations.
  • Achieved high scalability through a hierarchical IoT architecture.
  • Confirmed soft real-time feasibility for the proposed system.

Conclusions:

  • The proposed decentralized, mist-computing-based surveillance system offers a scalable and efficient solution for public safety.
  • Integration of IoT protocols and computer vision significantly enhances threat detection capabilities.
  • The system provides a robust framework for real-time monitoring and rapid response in critical environments.