Efficient surveillance and monitoring using the ELK stack for IoT powered Smart Buildings

Improving surveillance and monitoring mechanisms is among the foremost requirements of an IoT powered Smart Building. The massive potential of IoT to transform basic and essential services like power saving, security, maintenance and monitoring opens up endless possibilities for optimal use- cases in various spheres across the technological spectrum. The implementation of an IoT testbed is most effective and robust when equipped with a framework for dynamic data analysis and visualization which lays the ground for carrying out corrective feedback mechanisms in case of anomalous data that needs action. With a surfeit of data processing tools and frameworks available in the industry today, it becomes an important consideration to pick a solution that works best for a specific use case, given its unique requirements. We propose the deployment of an alternative to conventional data warehousing in the form of the Elasticsearch-Logstash-Kibana (ELK) stack to help achieve our objectives of efficient surveillance and monitoring - a framework that is effortlessly operable, even to those without much technical expertise, and helps collect, parse and index the data received from the appropriate sensors while also dynamically rendering them to the user in easily comprehensible visualizations. We provide information on setting up and operating a unique and comprehensive apparatus using a state-of-the-art framework to accomplish these objectives - starting with establishing the desired testbed, retrieving the requisite values through the sensors, performing indexing, analysis and visualization on the data using the Elasticsearch-Logstash-Kibana (ELK) stack to gain important insights on the parameters being measured and visualize them in real time - which helps initiate necessary action on the eventual goal of security.