Abstract
Surveillance system is a method of securing resources and loss of lives against fire, gas leakage, intruder, earthquake, and weather. In today’s time, people own home, farm, factory, office etc. It has become more crucial to monitor everything for securing resources and loss of lives against fire, gas leakage, intruder, earthquake. As a part of surveillance, monitoring weather is also essential. Climate change and agriculture are interrelated processes, Today's sophisticated commercial farming like weather monitoring, suffers from a lack of precision, which results huge loss in farm. Monitoring residential and commercial arenas throughout is an efficient technique to decrease personal and property losses due to fire, gas leakage, earthquake catastrophes. Internet of Things make it possible and can be implemented separately for each thing or site. But it is very difficult to monitor each site and have centralized access of it across the world. This arises the need of heterogenous system which will monitor all IoTs and perform decision making accordingly. IoT itself a large-scale thing. For single IoT application, sensors used are more in number. These sensors generate thousands of records for an instance of time, some of those are valuable and some requires just analysis. This huge amount of data on servers requires better data processing and analytics. Maintenance is also a critical task. Cloud extends these functionalities but storing all the data on cloud entail users to pay tremendous cost to the cloud service providers. This problem is catered by “CoTsurF” framework. This paper presents novel and cost effective “CoTsurF” framework, CoT-enabled robust Surveillance system using fog machine learning, a Proof-Of-Concept implementation of heterogenous and robust surveillance system based on internet of things and cloud computing by leveraging a groundbreaking concept of Fog machine learning that is Fog Computing and machine learning in Cloud of Things.
Image Recognition using Machine Learning for Security Surveillance System in BIT Campus
