AstroPlant Sentinel: Next-Gen Space AgricultureMonitoring and ADS

With the expanding role of humanity in outer space, sustainable food production becomes crucial. The success of space farming is determined as much by thecultivation of crops as by the rigorous monitoring and control of environmentalfactors. In this undertaking, we are pleased to offer you AstroPlant Sentinel, acombination of IoT technology with ADS custom-made for space farming. Ourresearch stresses the need for real-time environmental monitoring within spaceshuttles, where any deviations from environmental conditions may lead to plantillness and drop in crop yield. To address this challenge, we designed a miniature IoT environment equipped with three key sensors: Soil Moisture Sensor,Sensor for Temperature and Humidity, and Air Quality Sensor. Through intensive experiments and sensitivity analysis, we discover what are the thresholdsof these factors that are suitable for plant growth in space. However, recognizing the inherent variability and occasional aberrations in environmental data,we delve into the development and evaluation of three distinct machine learningmodels for anomaly detection: One-Class Support Vector Machines (OCSVM),Isolation Forest, and Density-Based Spatial Clustering of Applications with Noise(DBSCAN). Essentially, our results prove that DBSCAN outperforms other techniques in finding out the anomalies in fluctuating data. Lastly, our methodologyfor data visualization using a Software as a Service (SaaS) cloud platform isthoroughly detailed, which improves interpretability and enables informed decision making. This paper identifies the synergy between IoT-based monitoring and advanced anomaly detection, which is instrumental in enhancing both therobustness and efficacy of space agriculture attempts.