Feasibility of Energy Neutral Wildlife Tracking using Multi-Source Energy Harvesting

TL;DR

This paper demonstrates a multi-source energy harvesting system for wildlife tracking that ensures energy neutrality, enhances data collection, and is compatible with existing cellular networks, enabling sustainable and maintenance-free animal monitoring.

Contribution

It introduces a novel energy-neutral wildlife tracking system combining solar and kinetic harvesting, with an energy-aware scheduler and simulation framework for realistic evaluation.

Findings

Maintains energy-neutral operation under varying conditions.

Increases data yield and reliability over single-source systems.

Enables consistent GPS and activity sampling every two minutes.

Abstract

Long-term wildlife tracking is crucial for biodiversity monitoring, but energy limitations pose challenges, especially for animal tags, where replacing batteries is impractical and stressful for the animal due to the need to locate, possibly sedate, and handle it. Energy harvesting offers a sustainable alternative, yet most existing systems rely on a single energy source and infrastructure-limited communication technologies. This paper presents an energy-neutral system that combines solar and kinetic energy harvesting to enable the tracking and monitoring of wild animals. Harvesting from multiple sources increases the total available energy. Uniquely, the kinetic harvester also serves as a motion proxy by sampling harvested current, enabling activity monitoring without dedicated sensors. Our approach also ensures compatibility with existing cellular infrastructure, using Narrowband Internet of Things (NB-IoT). We present a simulation framework that models energy harvesting, storage, and consumption at the component level. An energy-aware scheduler coordinates task execution based on real-time energy availability. We evaluate performance under realistically varying conditions, comparing task frequencies and capacitor sizes. Results show that our approach maintains energy-neutral operation while significantly increasing data yield and reliability compared to single-source systems, with the ability to consistently sample GPS location data and kinetic harvesting data every two minutes while transmitting these results over NB-IoT every hour. These findings demonstrate the potential for maintenance-free, environmentally friendly tracking in remote habitats, enabling more effective and scalable wildlife monitoring.