Is Indoor Solar the Answer for IoT Sensor Power?
For IoT sensors to operate reliably in indoor environments, the choice of power supply method is critical. Especially in locations where maintenance is challenging or battery replacement is costly, solutions that enable self-generated power are gaining attention. Among these, indoor solar (Indoor PV) is one of the most promising options according to many experts.
Advantages of Indoor Solar
- Continuous Power Supply – In an office environment with 200–400 lux illumination, it can consistently generate 15–35 μW/cm² of power.
- Reduced Maintenance Costs – Longer battery replacement or recharge cycles lead to significant long-term savings.
- Eco-Friendly – Reduces fossil fuel-based electricity usage and contributes to lower carbon emissions.
Limitations and Considerations
- Output Limitations – In low-light or shaded areas, it may be difficult to secure sufficient power.
- Installation Location – Panels must be placed to receive the maximum possible light for optimal efficiency.
- Low-Power Design – Sensor firmware and hardware must be designed for ultra-low power consumption to ensure stable operation.
Comparing Indoor Solar with Other Energy Sources
While indoor solar can provide stable power in typical office conditions, its efficiency varies compared to alternatives such as thermoelectric generators (TEG), piezoelectric devices, and RF energy harvesting. For instance, in environments with high vibration, piezoelectric devices may be more suitable, while in areas with significant temperature differences, thermoelectric generators could be more effective.
Application Examples
Indoor solar power is being applied to various IoT devices such as temperature/humidity sensors in smart offices, occupancy detection sensors, and asset tracking tags. It is especially effective for ceiling-mounted or long-term installation devices that are hard to maintain.
Conclusion
Indoor solar has great potential as a power solution for low-power IoT sensors. However, since its efficiency is highly dependent on light conditions, prior environmental analysis and optimization of the sensor’s power consumption are essential.
