Energy-efficient ZigBee-based wireless sensor network for track bicycle performance monitoring.

Area of Science:

• Wireless Sensor Networks (WSNs)
• Biomedical Engineering
• Internet of Things (IoT)

Background:

• Power consumption is a critical challenge in wireless sensor networks (WSNs).
• Bike-mounted WSNs monitoring speed and cadence face high power demands due to continuous data transmission.
• Existing solutions often struggle to balance performance with energy efficiency.

Purpose of the Study:

• To develop and evaluate a novel algorithm for reducing power consumption in bike WSNs.
• To enhance the energy efficiency of sensor nodes without compromising data accuracy.
• To minimize hardware complexity and cost in bicycle monitoring systems.

Main Methods:

• Implementation of the Redundancy and Converged Data (RCD) algorithm.
• Data fusion of speed and cadence parameters leveraging their correlation.
• Minimization of data packet transmission to enable sensor node sleep modes.
• Utilizing the ZigBee protocol for wireless communication.

Main Results:

• The RCD algorithm reduced sensor node current consumption to 1.69 mA.
• Achieved a significant energy saving of 95% for the sensor node.
• Demonstrated minimal current consumption compared to other wireless technologies.
• Enabled effective data monitoring with reduced node count.

Conclusions:

• The proposed RCD algorithm offers a highly effective solution for power saving in bike WSNs.
• Data fusion and redundancy reduction are key to enhancing energy efficiency.
• This approach simplifies hardware, reduces costs, and improves overall system performance.