A temperature detection device includes: a detection processing unit configured to transmit a transmission radio wave, simultaneously receive a response radio wave corresponding to the transmission radio wave, and detect whether a temperature of an object to be measured is normal or abnormal based on the response radio wave; and a temperature sensing unit configured to receive the transmission radio wave and transmit the response radio wave responding to the transmission radio wave. The detection processing unit calculates, from the response radio wave received via a second antenna, an amplitude, a phase, or a quadrature phase amplitude of the response radio wave and compares the temperature of the object to be measured to a temperature determined in advance based on a result of the calculation.

A health of a server infrastructure is supervised by sending measurement requests, from a polling node to a server of the server infrastructure, at each of successive polling periods. Measurements received from the server in response to the measurement requests are stored in a database. A machine learning system is trained using accumulated measurements stored in the database to construct a prediction model for the server. Compliance of a latest measurement received from the server with the prediction model for the server is evaluated. A corrective action is taken if the latest measurement does not comply with the prediction model for the server. Measurements received from a group of servers may be aggregated and the machine learning system may construct a prediction model for the group of servers. Compliance to the prediction model may be evaluated for the group of servers.

A health of a server infrastructure is supervised by sending measurement requests, from a polling node to a server of the server infrastructure, at each of successive polling periods. Measurements received from the server in response to the measurement requests are stored in a database. A machine learning system is trained using accumulated measurements stored in the database to construct a prediction model for the server. Compliance of a latest measurement received from the server with the prediction model for the server is evaluated. A corrective action is taken if the latest measurement does not comply with the prediction model for the server. Measurements received from a group of servers may be aggregated and the machine learning system may construct a prediction model for the group of servers. Compliance to the prediction model may be evaluated for the group of servers.

A smart body temperature monitoring system, including a thermometer that has a body temperature detection module, a CPU connected with the body temperature detection module, and a wireless communication module connected with the CPU; a cloud server having a cloud database that stores global records of one or more persons including global identification information and global body temperature data of the person; and a mobile terminal, through which the global records of the cloud database stored in the cloud server are accessed and checked.

A smart body temperature monitoring system, including a thermometer that has a body temperature detection module, a CPU connected with the body temperature detection module, and a wireless communication module connected with the CPU; a cloud server having a cloud database that stores global records of one or more persons including global identification information and global body temperature data of the person; and a mobile terminal, through which the global records of the cloud database stored in the cloud server are accessed and checked.

A system for monitoring the characteristics of a material by measuring electrical properties of a material uses a material monitoring device and a cloud database that relates electrical properties of a material to characteristics of that material. The aging and fermentation processes of wine and other alcohols can be monitored. The status and decomposition of foodstuffs can be monitored. The progress of chemical reactions in a vessel can be monitored. Water quality of water from a water conduit can be monitored. These characteristics can be indicated on a product monitoring device or can be communicated to an external computing device.

Systems and methods for temperature monitoring and environmentally related calculations are disclosed herein. A system according to embodiments herein may include a memory, a network interface, and one or more processors. The system may receive one or more environmental readings from a sensor taking readings at an environmentally controlled area. The system may further determine a timestamp corresponding to each of the one or more readings and calculate, using the one or more readings and their corresponding timestamps, an exposure of a good stored within the temperature controlled area. The system may further determine that the calculated exposure of the good has surpassed a pre-determined exposure threshold for the good and send an electronic message configured to indicate such determination to a user. The system may use a neural network to predict future readings based on current readings and use the predicted future readings in methods described herein.

Systems and methods for temperature monitoring and environmentally related calculations are disclosed herein. A system according to embodiments herein may include a memory, a network interface, and one or more processors. The system may receive one or more environmental readings from a sensor taking readings at an environmentally controlled area. The system may further determine a timestamp corresponding to each of the one or more readings and calculate, using the one or more readings and their corresponding timestamps, an exposure of a good stored within the temperature controlled area. The system may further determine that the calculated exposure of the good has surpassed a pre-determined exposure threshold for the good and send an electronic message configured to indicate such determination to a user. The system may use a neural network to predict future readings based on current readings and use the predicted future readings in methods described herein.

The present disclosure relates to a monitoring system and method for wellsite equipment, used for monitoring abnormities in the monitoring area of wellsite equipment, wherein the monitoring system for wellsite equipment comprises: a dynamic capturing module comprising a video acquisition unit and a dynamic analysis unit, wherein, the video acquisition unit acquires video signals in the monitoring area of wellsite equipment, and the motion analysis unit analyzes and determines whether there is abnormal dynamic activity in the monitoring area of wellsite equipment based on acquired video signals; a temperature detection module comprising a temperature acquisition unit and a temperature analysis unit, wherein the temperature acquisition unit acquires temperature distribution in the monitoring area of wellsite equipment, and the temperature analysis unit analyzes and obtains temperature information in the monitoring area of wellsite equipment based on acquired temperature distribution, and determines whether there is temperature anomaly in the monitoring area of wellsite equipment based on the temperature information; and an information processing module configured to determine type of fault in the monitoring area of wellsite equipment based on considering the abnormal dynamic activity and the temperature anomaly separately or both.

The present disclosure relates to a monitoring system and method for wellsite equipment, used for monitoring abnormities in the monitoring area of wellsite equipment, wherein the monitoring system for wellsite equipment comprises: a dynamic capturing module comprising a video acquisition unit and a dynamic analysis unit, wherein, the video acquisition unit acquires video signals in the monitoring area of wellsite equipment, and the motion analysis unit analyzes and determines whether there is abnormal dynamic activity in the monitoring area of wellsite equipment based on acquired video signals; a temperature detection module comprising a temperature acquisition unit and a temperature analysis unit, wherein the temperature acquisition unit acquires temperature distribution in the monitoring area of wellsite equipment, and the temperature analysis unit analyzes and obtains temperature information in the monitoring area of wellsite equipment based on acquired temperature distribution, and determines whether there is temperature anomaly in the monitoring area of wellsite equipment based on the temperature information; and an information processing module configured to determine type of fault in the monitoring area of wellsite equipment based on considering the abnormal dynamic activity and the temperature anomaly separately or both.