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Abstract. Peanuts remain in-shell after harvest while they are dried and stored. A representative sample has to be extracted, cleaned of all foreign material, and shelled for kernel moisture content determination with the official moisture meter. Therefore, real-time determination of kernel moisture content during drying isn‘t feasible. Presently, there is no commercially-available moisture sensor for in-shell kernel moisture content determination at multiple locations within a semitrailer full of peanuts being dried, and there is an industry-wide need for such technology to improve the efficiency of drying and minimize instances of overdrying. Peanut-drying monitoring systems consisting of a microwave moisture sensor (developed within USDA ARS), two relative humidity sensors, and three temperature sensors have demonstrated real-time monitoring of in-shell kernel moisture content, temperature of the peanuts at the location of the microwave sensor, temperature of the drying and exhaust air, and relative humidity of the drying and exhaust air with 12-second resolution in the laboratory and while deployed at peanut buying points. In-shell kernel moisture content determination has been demonstrated with a standard error of performance (SEP) of ≤ 0.55% kernel moisture content. The monitoring systems were upgraded with wireless connectivity and implemented within a distributed network to provide remote monitoring of real-time results. ThingSpeak, an open-source Internet of Things (IoT) platform, was utilized to assign each sensor within the monitoring system with an application programming interface (API) and facilitate transmission of data to a centralized location, viewable graphically on any internet-enabled device. Each measured parameter was defined as a channel within ThingSpeak, and corresponding data were stored and transmitted from each system.