2018/08/20 by Lamar Burton, L. K. BURTON, Burton, Lamar +10
Agricultural and Biological Sciences · Computer Science · #Computers and Society (cs.CY) #FOS: Computer and information sciences #Smart Agriculture and AI #cs.CY
paper · pdf · doi:10.48550/arxiv.1808.07381
12 pages, 5 figures, published on 14th International Conference on Precision Agriculture
arxiv created 2018/08/20 · openalex publication_date 2018/08/20 · arxiv updated 2018/08/23 · openalex created_date 2018/08/31 · openalex updated_date 2026/07/28
The goal of this project was to explore commercial agricultural and irrigation sensor kits and to discern if the commercial wireless sensor network is viable tool for providing accurate real-time farm data at the nexus of food, energy and water. The smart garden consists of two different varieties of Abelmoschus esculentus planted in raised beds, each grown under two different fertilizer treatments. Soil watermark sensors were programmed to evaluate soil moisture and dictate irrigation events up to four times a day, while soil temperature and photosynthetic solar radiation sensors also recorded data every six hours. Solar panels harvested energy to power water pump and sensors. The objectives of the experiments were to evaluate and compare plant and soil parameters of the two okra varietes grown under two different fertilizer treatments. The plant parameters evaluated and compared were basal diameter, plant height, fruit production, and fruit size. Soil parameters measured were soil moisture, soil temperature, and soil nitrate concentration. The commercial sensors were evaluated on efficiency, accuracy, ease of use and overall practicality. Clemson spineless produced larger okra plants with the highest plant parameter values, followed by Emerald okra.