Authors: Wenjun Huang, Arghavan Rezvani, Hanning Chen, Yang Ni, Sanggeon Yun, Sungheon Jeong, Mohsen Imani

Published on: February 03, 2024

Impact Score: 8.38

Arxiv code: Arxiv:2402.02043

Summary

• What is new: A novel sensing module with intelligent data transmission capabilities for IoT applications, focusing on efficiency and selective data transmission.
• Why this is important: Current sensing systems in IoT lack targeted intelligence, leading to excessive data generation and higher computational and communication costs.
• What the research proposes: Integration of a highly efficient machine learning model near the sensor to regulate data transmission frequency and discard irrelevant data.
• Results: Over 85% system efficiency in terms of energy consumption and storage with negligible performance impact, significantly reducing data output from sensors.

Technical Details

Technological frameworks used: Customized training process, ‘lazy’ sensor deactivation strategy.

Models used: Quantized and optimized machine learning model for real-time sensor control.

Data used: Sensor-generated data.

Potential Impact

IoT applications across various industries, particularly those reliant on efficient data transmission and processing such as smart homes, healthcare monitoring, and industrial automation.

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