Publication Type:

Conference Proceedings


2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT) (2019)



Ambient intelligence, ambient intelligence-based decision support system, Anomaly detection, anomaly detection system, Bayesian nonparametric method (BNP), computer network security, Decision support systems, elderly assistance, electronic surroundings, face, Face recognition, Feature extraction, Hidden Markov model (HMM), home computing, home-based security, house holders, Internet of things, intruder detection, IOT, preventive maintenance, Principal component analysis, Principle component analysis (PCA), Security, Video surveillance


Ambient intelligence is an evolving discipline which brings intelligence to our daily life through various domains comprising elderly assistance, preventive maintenance, video surveillance, etc. It refers to the concept of electronic surroundings that are subtle and reactive to the existence of people or things. In the up-to-date society, criminality reaches out to influence most aspects of people's regular lives. Hence, individuals themselves started assuring against crime. This paper describes an ambient intelligence-based decision support system which provides home-based security. The proposed system mainly focuses on two techniques: face recognition to identify the house holders and anomaly detection to recognize the activities of the individual. Thus it can be used to send alerts to necessary authorities and family members if needed and enables real time monitoring of the captured anomaly through Internet of Things (IoT). The proposed framework produces an efficient face recognition and anomaly detection system with high performance rate.

Cite this Research Publication

K. Lashmi and Dr. Anju Pillai S., “Ambient Intelligence and IoT Based Decision Support System for Intruder Detection”, 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT). 2019.