A method and a system for providing one or more services to one or more user devices [202] in an IoT network in a scalable M2M (Machine to Machine) framework. The method comprises receiving a connection request from the one or more user devices [202] at a load balance of the IoT network, the connection request comprises at least a username comprising a cluster identifier. The load balancer [204] determines a cluster identifier based on the connection request and identifies at least one target cluster from the one or more clusters [206], said target cluster being associated with the identifier cluster identifier. The load balancer [204] routes the connection request to the at least one target cluster to provide the one or more services to the one or more user devices [202].

An electronic device may include: a communication module; a processor operatively connected to the communication module; and a memory operatively connected to the processor and configured to store computer program code. The computer program code, when executed, enables the processor to: upon detection of execution of a first operation of a first Internet of Things (IoT) device, obtain, from the memory, a first instruction to operate the first IoT device in a second operation; transmit the first instruction to the first IoT device to operate the first IoT device in the second operation; and monitor execution of the second operation by the first IoT device.

A method and a system for providing one or more services to one or more user devices

in an IoT network in a scalable M2M (Machine to Machine) framework. The method comprises receiving a connection request from the one or more user devices [202] at a load balance of the IoT network, the connection request comprises at least a username comprising a cluster identifier. The load balancer [204] determines a cluster identifier based on the connection request and identifies at least one target cluster from the one or more clusters [206], said target cluster being associated with the identifier cluster identifier. The load balancer [204] routes the connection request to the at least one target cluster to provide the one or more services to the one or more user devices [202].

A live web camera feed and streaming transmission system and method for gathering, identifying and authenticating biometric data of a specific human being while constantly monitoring, tracking, analyzing, storing and distributing dynamic biometric data to ensure authorized access to the secured system continues via positive live feed monitoring of biometric data for participating computer systems and or programs. Multiple, correlative, inseparable, embedded serial numbers allow for editing within a live video recording session because the serial numbers are “attached” to one another from frame to frame. The degree of identity verification correlated with the various serial numbers, directly affects an indelible, detectible, identity verification cumulative authentication rating score in conjunction with a recognizable and standardized, indelible, detectible, hyperlinked color-coded security badge displaying the degree of identity authentication. If any one of these components that work cooperatively and correlatively is tampered with in any regard, the video is rendered inoperable.

The invention discloses a SMART, portable internet of thing (IoT) based device and/or system to monitor various key parameters automatically, in a given operating area or operating system in various application fields, which automatically performs multiple monitoring functions such as sampling, measuring, analyzing, reporting and stabilizing key controllable parameters and there auto-maintain these parameters as per desired level. The SMART, portable device and system of the invention can be used in many applications in various fields such as Bio-Medical, Agriculture, Waste Treatment, Distilleries, RO Plants, etc, to name a few, where maintaining the key parameters like, pH, EC, Temperature, etc, are key for higher yields and/or efficient/smooth functioning and there these key parameters are required to be controlled.

An Internet-of-Things module is provided, comprising a first interface, via which the module can be coupled to a hybrid single pair Ethernet line for exchanging data and/or commands and for supplying voltage. The module also has a voltage regulator for converting the first voltage applied at the first interface into a second voltage for supplying the module. A controller is also provided for IP-based communication via the hybrid single pair Ethernet line. A second interface is also provided, via which the module can be coupled to a sensor and/or actuator for exchanging data, signals and/or commands and for supplying voltage.

Co-clustering of at least some parameters is employed to reduce data transferred between edge and cloud resources. Single-parameter cluster information, including cluster counts, for each of two or more parameters of interest is accessed. Each parameter may represent a time series of numeric values sent from an IoT unit to an edge device. A co-clustering ratio is determined for each unique parameter pair. The co-clustering ratio indicates whether the number of clusters produced by a co-clustering algorithm applied to a group of parameters is less than the number of clusters required to represent the parameters without co-clustering. Co-cluster groups may be identified based on the cluster ratios. For each co-cluster group, the co-clustering algorithm may be invoked to produce compressed encodings of numeric value tuples. The compressed encoding is then transmitted to a cloud computing resource and decoded into a tuple of surrogate values.

The disclosure relates to an information processing method and apparatus, a computing device, a medium, and a computer program. In some embodiments, the information processing method includes: defining an IOT semantic model file of a specific object using an existing IOT semantic model; generating an OPC UA information model based on the IOT semantic model file; parsing the OPC UA information model into an OPC UA protocol-compliant file; and generating a source code available for an OPC UA protocol stack using an adapter based on the OPC UA protocol-compliant file.

A distributed device management system specifies a device capable of supplying request data used for providing a service, from among a plurality of devices connected to a network. Device management function units are disposed so as to be geographically distributed and manage the states of the devices located in deployed areas. A device specifying function unit has a device inquiry cache in which a response log including the type of data which was previously required for the service and an identifier of the device management function unit that manages the device which was capable of supplying the data is recorded. In a case where this request data coincides with the type of data included in the response log, an inquiry is transmitted to the device management function unit associated with the request data in the response log.

A distributed device management system specifies a device capable of supplying request data used for providing a service, from among a plurality of devices connected to a network. Device management function units are disposed so as to be geographically distributed and manage the states of the devices located in deployed areas. A device specifying function unit has a device inquiry cache in which a response log including the type of data which was previously required for the service and an identifier of the device management function unit that manages the device which was capable of supplying the data is recorded. In a case where this request data coincides with the type of data included in the response log, an inquiry is transmitted to the device management function unit associated with the request data in the response log.