Towards the Implementation of IoT for Environmental Condition Monitoring in Homes

TLDR

The system uses a distributed network of smart sensors, an integrated architecture for data aggregation and context‑aware reasoning, and real‑time graphical output to reliably monitor home environmental conditions. The low‑cost IoT system achieved 97 % reliability in transmitting sensing data, and its longitudinal learning component enabled self‑control for improved device operation during monitoring.

Abstract

In this paper, we have reported an effective implementation for Internet of Things used for monitoring regular domestic conditions by means of low cost ubiquitous sensing system. The description about the integrated network architecture and the interconnecting mechanisms for the reliable measurement of parameters by smart sensors and transmission of data via internet is being presented. The longitudinal learning system was able to provide a self-control mechanism for better operation of the devices in monitoring stage. The framework of the monitoring system is based on a combination of pervasive distributed sensing units, information system for data aggregation, and reasoning and context awareness. Results are encouraging as the reliability of sensing information transmission through the proposed integrated network architecture is 97%. The prototype was tested to generate real-time graphical information rather than a test bed scenario.