Smart Home Wireless Sensor Nodes Addressing the Challenges using Smart Objects and Artificial Intelligence

TL;DR

This paper presents an innovative approach using smart objects with AI to reduce power consumption and network load in wireless sensor nodes for smart homes, enhancing efficiency and reducing interference.

Contribution

It introduces a novel method that employs AI-enabled smart objects to locally process sensor data, significantly lowering wireless transmission and power use in smart home sensor networks.

Findings

Significant reduction in sensor node power consumption.

Decreased wireless network load and interference.

Efficient local processing of sensor events.

Abstract

Smart homes are further development of intelligent buildings and home automation, where context awareness and autonomous behaviour are added. They are based on a combination of the Internet and emerging technologies like wireless sensor nodes. These wireless sensor nodes are challenging because they consume battery power, they use network bandwidth, and they produce wireless interferences. Currently, different methods exist for handling these challenges. These methods are, however, based on adjusting the transmitter frequency and using duty-cycling in combination with sleep mode approaches. This paper introduces an approach that considerably lowers the wireless sensor node power consumption and the amount of transmitted sensor events. It uses smart objects that include artificial intelligence to efficiently process the sensor event on location and thereby saves the costly wireless transportation of these events. In this paper it has been shown that this approach provides huge savings of power consumption and network load, which in turn reduces the interference level