Information-Aware Sensing Framework for Long-Lasting IoT Sensors in Greenhouse.

A sensor network is an underpinning infrastructure that enables various future IoT applications, such as precision agriculture, smart farm, and greenhouse monitoring. However, these sensor devices often suffer from short-lived battery lifetime that incurs frequent maintenance operation. Although there have been a few attempts to smartly reduce the power consumption associated with communication tasks of the sensors, very few have addressed the power consumption of sensing tasks. In light of this shortcoming, we propose an information-aware sensing framework that adaptively adjusts the sensing interval for energy-saving operations based on the learned behavior of the sensor data. To prove the effectiveness of the proposed framework, we have deployed four BLE beacons equipped with luminosity and temperature sensors to collect real-life data from a desert greenhouse, which is then used to train and evaluate our proposed framework. Additionally, we have implemented the proposed framework on a commodity BLE beacon device to validate the energy-saving performance of the proposed framework. The results demonstrate that the proposed framework can effectively reduce the energy consumption involved in sensing tasks by 30% and extend the battery lifetime by up to 75%.