Abstract: Systems for determining the moisture level in non-polar materials, such as polymers, include an electrical circuit including a capacitive sensor, and a signal generator that the provides the electrical circuit with an electrical input of varying frequency. The systems also include a computing device the determines the moisture level in the non-polar material based on a relationship between the moisture level, and a response of the electrical circuit to the electrical input while the capacitive sensor is in contact with the non-polar material.

Abstract: A field learning system comprising a system of feedback using a user interface in a web based and mobile application to overcome the difficulty and infeasibility of supervised machine learning systems used for modeling failure states of machines.

Abstract: A machine learning method and system for predictive maintenance of a dryer. The method includes obtaining over a communication network, an information associated with the dryer and receiving measurements of a vibration level of one of a process blower, a cassette motor and a regeneration blower associated with the dryer. Further, an anomaly is determined based on at least one of a back pressure and a fault and balance of at least one of the process blower and the regeneration blower is tracked. An alarm for maintenance is raised when one of an anomaly and an off-balance is detected.

Abstract: A machine learning method and system for predictive maintenance of a dryer. The method includes obtaining over a communication network, an information associated with the dryer and receiving measurements of a vibration level of one of a process blower, a cassette motor and a regeneration blower associated with the dryer. Further, an anomaly is determined based on at least one of a back pressure and a fault and balance of at least one of the process blower and the regeneration blower is tracked. An alarm for maintenance is raised when one of an anomaly and an off-balance is detected.

Abstract: Disclosed is an IoT-based system for overseeing process control and predictive maintenance of a machine or a network of machines by employing machine wearable sensors. The system comprises a plurality of IR temperature sensors, each of which secured to the exterior of the machine; each IR sensor capable of transmitting captured temperature data wirelessly over a communications network, an algorithm engine capable of receiving data from the IR sensors, the algorithm engine for further processing the received data to recognize real-time temperature patterns, deviations, etc., and based on the same issuing control commands pertaining to the machine, and one or more control modules disposed in operative communication with the control panel of the machine, the control module capable of receiving, over a communications network, the control commands and executing the same resulting in accomplishing process control or predictive maintenance of the machine or both.

Abstract: An automated earth fault testing system and early warning system designed to be used with mobile towers for real-time monitoring of the earthing values. The automated earth fault testing system comprises an earth fault testing device powered by a low voltage direct current battery, a plurality of terminals, at least one calibration switch including a calibration pad for calibrating the earth fault testing device, a plurality of visual indication means for providing indication of a variety of conditions including high and/or normal value of the earth resistance value and for indicating a charge level of the earth fault testing device and a liquid crystal display for displaying the earthing values. The earth fault testing device is connected to an alarm system of a base transceiver station utilizing a relay for informing the mobile signal station and operator with information regarding a status of the earth fault testing device.