Energy Harvesting in Self-Powered IOT Applications Domains

Abstract

The rapid growth of the Internet of Things (IoT) has led to the deployment of billions of interconnected devices that continuously sense, process, and communicate data. However, the reliance on conventional batteries poses major challenges in terms of maintenance, limited lifespan, and environmental impact. Energy harvesting offers a sustainable solution by converting ambient energy sources—such as solar, thermal, vibration, and radio frequency (RF) energy—into electrical power to enable self-powered IoT systems. This paper presents a comprehensive study of energy harvesting techniques and their integration into IoT application domains, including industrial monitoring, smart agriculture, healthcare, and environmental sensing. The proposed framework focuses on optimizing power management circuits, storage elements, and communication protocols to achieve high energy efficiency and prolonged device lifetime. Experimental and simulation results demonstrate the feasibility of hybrid energy harvesting systems that combine multiple ambient sources to ensure continuous operation even under variable environmental conditions. The findings highlight that energy harvesting not only enhancces system reliability but also paves the way toward a sustainable, maintenance-free, and scalable IoT ecosystem.

Introduction

The Internet of Things (IoT) connects billions of devices across sectors like smart cities, healthcare, agriculture, and industrial automation. Most IoT nodes rely on batteries, which are limited by capacity, require maintenance, and pose environmental concerns. Energy harvesting offers a sustainable alternative, converting ambient energy into electrical power to enable maintenance-free, self-powered IoT devices.

Key Concepts

1. Energy Harvesting Techniques

• Solar: High energy density; ideal for outdoor monitoring; limited indoors.

• Vibration: Piezoelectric, electromagnetic, and electrostatic mechanisms; efficient in industrial and transportation settings.

• Thermal: Thermoelectric generators exploit temperature gradients; suitable for wearable and industrial IoT.

• RF (Radio Frequency): Captures ambient electromagnetic waves; useful for low-power devices in urban areas.

• Hybrid Systems: Combine multiple sources (solar, vibration, RF) for reliable power under variable conditions.

2. Power Management and Storage

• Power management circuits: MPPT algorithms and ultra-low-power PMICs optimize energy extraction.

• Energy storage: Supercapacitors and thin-film batteries buffer energy for peak loads.

• Adaptive duty-cycling: Sensors and communication modules adjust operation based on available energy.

3. Applications

• Smart Agriculture: Autonomous monitoring of soil and crops.

• Healthcare: Wearables powered by thermal or kinetic energy for continuous patient monitoring.

• Industrial IoT: Structural health monitoring using vibration and RF energy.

• Environmental Monitoring: Remote, autonomous sensor networks.

4. System Architecture

• Components include energy sources, harvesting modules, power management and storage, and IoT nodes.

• Supports hybrid energy configurations and low-power communication protocols (LoRa, BLE, Zigbee).

• Adaptive energy allocation ensures operation during low-energy periods.

5. Construction and Working

1. Energy Capture: Ambient sources (solar, vibration, thermal, RF) are harvested by transducers.

2. Energy Conversion & Regulation: Transducers convert energy to DC and regulate voltage.

3. Storage & Management: Supercapacitors/microbatteries store energy; PMU manages distribution.

4. IoT Node Operation: Powers sensors and communication modules; low-power mode activated when energy is scarce.

5. Data Transmission: Collected data sent to cloud/server for monitoring and control.

6. Advantages

• Battery-less operation reduces maintenance costs.

• Sustainable, eco-friendly energy use.

• Continuous autonomous operation, even in remote locations.

7. Experimental Results

• Solar PV: 120 mW output under standard illumination.

• Vibration: 1.5–2.2 mW from 50–100 Hz vibrations.

• Thermal: 3.8 mW at 20°C gradient.

• Power management efficiency: 85%; supercapacitor enabled 18 hours operation in low-energy conditions.

• IoT node operated autonomously for over three weeks in real-time testing.

• Hybrid harvesting improved reliability and reduced downtime.

8. Research Gaps

• Intermittent and low-power nature of ambient sources limits high data-rate applications.

• Integrating multiple sources while minimizing cost and complexity is challenging.

• Energy-aware communication protocols need optimization.

Conclusion

The research successfully demonstrated the design and implementation of a self-powered IoT system utilizing multiple energy harvesting techniques. The proposed framework effectively integrates solar, thermal, and vibration-based energy sources with an optimized power management unit and energy storage system. Experimental results verified that the hybrid harvesting approach provides a stable and continuous power supply to IoT nodes, even under fluctuating environmental conditions. This enables long-term, maintenance-free operation of IoT devices, reducing battery dependency and promoting environmental sustainability.

References

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Copyright

Copyright © 2025 Mrs. Yuvasri P, Mrs. Manju R, Mrs. Amsaveni A. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.