CLAY-MIST: IoT-cloud enabled CMM index for smart agriculture monitoring system

Abstract The temperature and soil moisture factors affect the growth of agriculture such as productivity, diseases, and yield production. Most of the existing techniques were used to assess comfort level based on dew-point-humidity data which gives a false decision with time and energy consumption. To comprehend these issues, we proposed a cloud-enabled CLAY-MIST measurement (CMM) index based on temperature and relative humidity to assess the comfort levels of a crop. In this research, temperature quotient is evaluated based on the amount of water vapour and pressure in the air which appraises plant growth. The relative humidity is subtracted with the standard constant optimal temperature to extract the comfort level. Therefore, the CMM index experiments with real-time data show an accurate decision and the detailed report sent to farmers. The results are 94% accurate with less execution time when compared with the existing thermal comfort techniques.