The Design and Evaluation of an IoT Tracker for Carbon Footprint Verification on Agricultural Machinery

To reduce the problem of labor shortage in agriculture, machinery has become an important solution worth of investment. In Taiwan, the government has approved an annual investment of NT$2.3 billion starting from 2022 to support the application of agricultural machinery. According to the statistics provided by the Ministry of Agriculture (MOA), the number of agricultural machinery in Taiwan has exceeded 200,000, and most of them are powered by gasoline. As more and more emphasis is put on ESG in recent years, the issue of carbon footprint verification (CFV) in agriculture begins to draw worldwide attention. To understand the carbon footprint of agricultural products, it is obvious that the carbon emission of agricultural machinery must be tracked. However, it is usually not easy for farmers to complete the CFV on their machinery, since they are not experts in greenhouse gas (GHG) accounting. In this paper, we design an IoT tracker to accomplish the CFV on agricultural machinery. This tracker combines a GPS, a G-sensor, and a Cat-M1 module, so that the movement and vibration signal of machine can be detected and transmitted to our cloud system. The obtained data is used for estimating the amount of consumed gasoline, which turns out to be carbon emission according to the standard of ISO 14064. We evaluate the performance of our tracker in three different modes, which are (1)GPS only, (2)G-sensor only, and (3)GPS plus G-sensor. Our experimental results show that the third mode achieves the best accuracy, which suggests that for the purpose of CFV on agricultural machinery, G-sensor can provide good calibration to GPS tracker.