Integrating artificial intelligence and computer learning into the SolaRid monitoring device to create a comprehensive decision-making support system

Project Summary/Abstract. The Company proposes to research the feasibility of reducingchemical insecticide and labor required while increasing the data collected using advancedimaging propietary artificial intelligence and attractants in monitoring detecting and managingagricultural pests over the 8-month project period. This research specifically targets Amyeloistransitella aka Navel Orangeworm (NOW) the primary pest in California almonds whichcauses more than $900M of annual losses. The SolaRidâ„¢ product applies algorithms todetermine crop phenology and timing of insects biofix events while monitoring abioticconditions with sensors. It utilizes five interchangeable insect attractant modules to lure specifictargeted pests. Finally aproprietary artificial intelligence (AI) technology developed by anawarded National Science Foundation (NSF) grant is used to detect target species infestationscompleting a comprehensive analytic decision support system. More efficient insect control willresult from the quality of data analyzed by SolaRid allowing for reduced chemical insecticideuse by increasing the specificity and timeliness of the applied input. More finely attunedapplications in time and space will reduce residuals on produce and the amount of insecticides inour environment. EPA licensed agricultural Pest Control Advisors (PCA) are becoming moredependent on sensors and remotely generated data. SolaRid's use is consistent with this trendimproving the quality/ accessibility of data saving up to 6 hours/day of in-field monitoring datais available 24 hours/7 days a week remotely.Project Objectives and a Description of the Effort. SolaRid will conduct the field trials withUC ANR. The objective is to test the AI technology to develop empirical data of the combinedtechnologies' efficacy.The initial steps include setting up communication networks calibratingsensors and confirming protocols. Then while the device is being tested the Company will elicitproduct design and procedural recommendations from PCA's and producers. An example ofhow this process would work for adjusting the algorithm is broadly outlined at the end of theTechnical Objectives section. There are five research questions concerning validity benefits andperformance of the sensor outputs and procedures. Results are intended to create actionableintelligence for data driven management decisions developed during this phase I research.Inphase II the Company will continue to collaborate with its California partners to complete theinsect control device (ICD) creating a complete and sustainable turn-key solution. At the end ofphase II we will have multiple fully functional units to competently identify and count localinsects and identify key agricultural pests of high economic importance in nut orchard industry.