A cloud server including a communication interface; and at least one processor configured to: detect a plurality of IoT devices connected to the cloud server from the communication interface, based on detecting the plurality of IoT devices connected to the cloud server, determine that the plurality of IoT devices are equipped with a corresponding plurality of intelligence engines, read and store a plurality of intelligence engine types of the plurality of intelligence engines, obtain a plurality of online states of the plurality of IoT devices, receive a search instruction sent from a receiving IoT device of the plurality of IoT devices, identify an instruction type of the search instruction, and store a correspondence between the instruction type and a preferred intelligence engine type, and select an IoT device based on the correspondence.

A cloud server including a communication interface; and at least one processor configured to: detect a plurality of IoT devices connected to the cloud server from the communication interface, based on detecting the plurality of IoT devices connected to the cloud server, determine that the plurality of IoT devices are equipped with a corresponding plurality of intelligence engines, read and store a plurality of intelligence engine types of the plurality of intelligence engines, obtain a plurality of online states of the plurality of IoT devices, receive a search instruction sent from a receiving IoT device of the plurality of IoT devices, identify an instruction type of the search instruction, and store a correspondence between the instruction type and a preferred intelligence engine type, and select an IoT device based on the correspondence.

A method of predicting evolution of simulation results for an Internet of Things (IoT) network comprising creating a source digital twin outputting a state of object(s). A main digital twin sequence is formed by creating clone digital twin(s), connecting an input of one clone digital twin with an output of the source digital twin where a time increment is added to the output of the source digital twin and connecting an input of any further clone digital twin with an output of a preceding clone digital twin where a further time increment is added to the output of the preceding clone digital twin. An evolved modified state of the object(s) is provided at additionally incremented time as an output of an exploratory digital twin which has an input connected with an output of one of the source digital twin, the one clone digital twin, and any further clone digital twin.

A method for optimizing power consumption for Narrowband Internet of Things devices, UEs, in idle mode using a coverage class specific paging configuration, where carriers for paging are partitioned by coverage class, whereas the coverage class specific paging configuration, broadcasted by a system information exchanged between the base station and the UE, is extended by an additional NRSRP rsrp-ThresholdPcch threshold, whereas the UE selects one carrier for paging with a Narrowband Reference signal received power (NRSRP) smaller than the rsrp-ThresholdPcch threshold or if a UE is not reachable the eNodeB expands a paging area for the considered UE stepwise into other paging coverage classes in order to reach the UE.

A method for optimizing power consumption for Narrowband Internet of Things devices, UEs, in idle mode using a coverage class specific paging configuration, where carriers for paging are partitioned by coverage class, whereas the coverage class specific paging configuration, broadcasted by a system information exchanged between the base station and the UE, is extended by an additional NRSRP rsrp-ThresholdPcch threshold, whereas the UE selects one carrier for paging with a Narrowband Reference signal received power (NRSRP) smaller than the rsrp-ThresholdPcch threshold or if a UE is not reachable the eNodeB expands a paging area for the considered UE stepwise into other paging coverage classes in order to reach the UE.

Aspects of the invention are directed towards a system and a method for uniformly characterizing equipment category. One or more embodiments of the invention describe the method comprising steps of extracting a plurality of data points from data stream received from a plurality of equipment within an equipment category. The method also comprises steps of normalizing the varying frequency of the extracted data points to generate time normalized information corresponding to each of the plurality of equipment. The method comprises steps of manipulating a plurality of variances in the translated uniform data stream received from each of the plurality of equipment within the equipment category. The method comprises steps of generically mapping the normalized information to one or more aggregation methods and for mapping the output of aggregation methods to one or more reusable data processing algorithms to generate a plurality of uniform equipment characteristics corresponding to the equipment category.

Aspects of the invention are directed towards a system and a method for uniformly characterizing equipment category. One or more embodiments of the invention describe the method comprising steps of extracting a plurality of data points from data stream received from a plurality of equipment within an equipment category. The method also comprises steps of normalizing the varying frequency of the extracted data points to generate time normalized information corresponding to each of the plurality of equipment. The method comprises steps of manipulating a plurality of variances in the translated uniform data stream received from each of the plurality of equipment within the equipment category. The method comprises steps of generically mapping the normalized information to one or more aggregation methods and for mapping the output of aggregation methods to one or more reusable data processing algorithms to generate a plurality of uniform equipment characteristics corresponding to the equipment category.

Propagation of pathogens is reduced by configuring internet of things (IoT) sensors along a supply chain of package; and analyzing the packages in the supply chain using the IoT sensors to determine handling requirements of products. The packages can be tracked with a package handling confirmation engine including a Region Based Convolutional Neural Network (RCNN) to determine with the IoT sensors measuring interactions with the packages that parties in the supply chain are handling the packages in accordance with the handling requirements. Product distribution can be stopped through the supply chain in response to the interactions with the packages failing to meet the handling requirements.

Propagation of pathogens is reduced by configuring internet of things (IoT) sensors along a supply chain of package; and analyzing the packages in the supply chain using the IoT sensors to determine handling requirements of products. The packages can be tracked with a package handling confirmation engine including a Region Based Convolutional Neural Network (RCNN) to determine with the IoT sensors measuring interactions with the packages that parties in the supply chain are handling the packages in accordance with the handling requirements. Product distribution can be stopped through the supply chain in response to the interactions with the packages failing to meet the handling requirements.

A method and a smart gas Internet of Things system for maintenance scheduling and management based on gas safety are provided. The method may comprise the following operations. Gas-related features of at least one area may be obtained, alert vectors of the at least one area may be determined based on the gas-related features, the alert vectors including a leakage alert value, a count of on-call maintenance personnel in the at least one area based on the alert vectors may be determined, whether the count of on-call maintenance personnel meets a preset threshold may be determined, in response to a determination that there is at least one area where the count of on-call maintenance personnel meets the preset threshold, a real-time scheduling policy based on a scheduling capability value of the at least one area where the count of on-call maintenance personnel meets the preset threshold may be determined.