An Intelligent real-time occupancy monitoring system using single overhead camera

Jawad Ahmad, Hadi Larijani*, Rohinton Emmanuel, Mike Mannion, Abbas Javed

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)


Real-time occupancy monitoring information is an important component in building energy management and security. Advances in technology enables us to develop vision-based systems. These systems have gained popularity among different scientific research communities due to their high accuracy. Based on real-time video from a single camera, people occupancy rates in buildings can be correctly estimated using neural network models. This paper proposes an intelligent real-time bidirectional system, using Random Neural Network (RNN) predictions. An overhead camera was used to capture RGB images and the number of people crossing a virtual line was counted using the proposed counting technique. The proposed algorithm extracts some important features such as occupant blob areas, major axis, minor axis, eccentricity, perimeters and area-perimeter ratio for total 1000 frames. Finally, a RNN model is trained with aforementioned features using a gradient decent algorithm. Real-time experimental results show the effectiveness of the proposed method, especially when occupants are in group and blob merge/split scenarios. Real-time testing revealed an accuracy between 100 and 93.38% for single and multiple occupants, respectively.
Original languageEnglish
Title of host publicationIntelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2
EditorsKohei Arai, Supriya Kapoor, Rahul Bhatia
PublisherSpringer Nature
Number of pages13
ISBN (Electronic)9783030010577
ISBN (Print)9783030010560
Publication statusPublished - 2019
EventIntelligent Systems Conference 2018 - London, United Kingdom
Duration: 6 Sept 20187 Sept 2018

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


ConferenceIntelligent Systems Conference 2018
Abbreviated titleIntelliSys 2018
Country/TerritoryUnited Kingdom
Internet address


  • occupancy
  • video camera
  • video processing
  • neural network
  • image features
  • blob areas
  • Kalman filter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science


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