Yield Monitoring Service with Time Series Representation of Growth from Crop Images

Due to the development of ICT technology and the explosion of data, various technologies such as smart farms and smart greenhouses have been applied to the agricultural sector, helping farmers a lot. This paper aims to process and utilize crop image datasets collected periodically from a strawberry greenhouse cultivation environment to analyze and monitor crop growth and yields. In addition to the time-series data collected by measuring environmental variables such as temperature, humidity, light intensity, and carbon dioxide concentration, growth-related data are needed to monitor fruit growth and predict yield. Rail cameras were installed on the testbed to collect image data on strawberry every certain time in a specific section, and to construct a time-series image dataset by detecting objects for each stage of strawberry growth. Due to the characteristics of strawberries, we represented the crop images into growth monitoring data applied to the entire fruit of the testbed or crop clusters, not to each fruit. In addition, it can be useful for various use cases if the represented growth-related time series data and sensor data are properly used together.