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A Mathematical Programming Approach for IoT-Enabled, Energy-Efficient Heterogeneous Wireless Sensor Network Design

Ertugrul Taparci¹, Kardelen Olcay¹, Melike Ozlem Akmandor¹

¹Faculty of Engineering and Natural Sciences, Istanbul Bilgi University, 34060 Istanbul, Türkiye.

Sensors (Basel, Switzerland)

|March 13, 2024

Summary

This summary is machine-generated.

This study optimizes Wireless Sensor Networks (WSNs) deployment in agriculture using a heterogeneous network model. The two-stage approach enhances energy efficiency, network longevity, and reliable data for smart farming.

Keywords:

data loss avoidance energy efficiency internet of things mathematical programming narrow-band communication optimization smart farming wireless sensor network

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Published on: December 9, 2012

Area of Science:

Agricultural Technology
Network Engineering
Internet of Things (IoT)

Background:

Wireless Sensor Networks (WSNs) are crucial for the Internet of Things (IoT) transformation.
Optimizing sensor deployment in agriculture is vital for efficiency and sustainability.
Heterogeneous network models offer potential for enhanced WSN performance.

Purpose of the Study:

To optimize sensor node deployment in agricultural settings using a heterogeneous network model.
To improve energy efficiency, network lifetime, and data transmission reliability.
To address connectivity, coverage, and real-time adaptability challenges in WSNs.

Main Methods:

A two-stage centralized control model incorporating offline and online optimization.
Grouping sensor nodes into 'boxes' for shared resource utilization and cost-effectiveness.
Simulations on agricultural farmland and hardware tests for validation.

Main Results:

The proposed model effectively addresses connectivity and coverage issues.
Significant improvements in energy efficiency through sensor consolidation and reduced data hops.
Validated practicality for real-world applications like soil temperature and humidity monitoring.

Conclusions:

The heterogeneous network model offers a practical solution for WSN deployment in agriculture.
This research contributes to the advancement of smart farming and sustainable agricultural practices.
WSNs have the potential to revolutionize agricultural monitoring and management.