Abstract: A method for detection of a corrupted sensor including providing a first sensor; identifying one or more correlating sensors to the first sensor; determining a correlation between the first sensor and the correlating sensors according to historical sensor values; obtaining a calculated value of the first sensor based on values of the correlating sensors and the correlation; obtaining a measured value of the first sensor; and determining whether the first sensor is corrupted according to a difference between the calculated value and the measured value of the first sensor.

Abstract: In some implementations, a digital twin system may receive, from one or more sensors and at an interface associated with a digital twin, a first input associated with a first event. The digital twin system may determine that the first event is associated with one or more probable second events. Accordingly, the digital twin system may refrain from processing the first input for a period of time. The digital twin system may further update a prediction associated with the digital twin using the first input based on expiry of the period of time or may update a prediction associated with the digital twin using second input associated with the one or more probable second events based on receiving the second input.

Abstract: This disclosure relates to a method and system for identifying products using digital fingerprints. The method includes receiving, by a product tracking system, a set of images corresponding to a product, wherein the set of images are received along with associated context information. The method generates a set of standardized images by pre-processing the set of images. Each standardized image of the set of standardized images are further segmented into a plurality of zones. A zone wise fingerprint is generated for each zone of the plurality of zones. A product digital fingerprint is generated for the product by combining zone wise fingerprints associated with the set of standardized images, wherein the product digital fingerprint identifies the product.

Abstract: This disclosure relates to method and system for identifying products using digital fingerprints. The method includes receiving, by a product tracking system, a set of images corresponding to a product, wherein the set of images are received along with associated context information. The method generates a set of standardized images by pre-processing the set of images. Each standardized image of the set of standardized images are further segmented into a plurality of zones. A zone wise fingerprint is generated for each zone of the plurality of zones. A product digital fingerprint is generated for the product by combining zone wise fingerprints associated with the set of standardized images, wherein the product digital fingerprint identifies the product.

Abstract: A method and device for automatically generating personalized smart contracts is disclosed. The method includes identifying a plurality of asset attributes associated with a current asset within a blockchain network. Each of the plurality of asset attributes are compared with each of a plurality of asset clusters to compute a cluster similarity score, when a plurality of assets within the blockchain network do not include the current asset. The method includes identifying an asset cluster that has the highest cluster similarity score and which is also above a predefined threshold. Similarity scores are then computed for each of the set of assets within the asset cluster. At least one asset from the set of assets is then identified based on the associated similarity scores. A current smart contract template is generated based on at least one smart contract template associated with the at least one asset.

Abstract: A device may receive sensor data from one or more sensor devices. The device may detect a trigger condition, that triggers an update to a model used to analyze the sensor data, based on receiving the sensor data. The trigger condition may include at least one of: a change in a type of data included in the sensor data, a change in an entity being monitored in association with the sensor data, or a change in a frequency with which the sensor data is received from the one or more sensor devices. The device may transmit a request to update the model based on detecting the trigger condition. The device may receive an updated model based on transmitting the request to update the model. The device may apply the updated model to the sensor data and/or subsequent sensor data received from the one or more sensor devices.

Abstract: A device may receive, from a consumer device, an application programming interface (API) request that includes information associated with a consumer of data and information associated with a producer of the data. The data may be collected by one or more data sources associated with the producer. The device may identify a consumer context, associated with the consumer, based on the information associated with the consumer. The device may identify a producer context, associated with the producer, based on the information associated with the producer. The device may generate an API response based on the consumer context and the producer context. The API response may include data in accordance with the consumer context and the producer context. The device may provide, to the consumer device, the API response to permit the consumer to view or access the data.

Abstract: A device may receive sensor data from one or more sensor devices. The device may detect a trigger condition, that triggers an update to a model used to analyze the sensor data, based on receiving the sensor data. The trigger condition may include at least one of: a change in a type of data included in the sensor data, a change in an entity being monitored in association with the sensor data, or a change in a frequency with which the sensor data is received from the one or more sensor devices. The device may transmit a request to update the model based on detecting the trigger condition. The device may receive an updated model based on transmitting the request to update the model. The device may apply the updated model to the sensor data and/or subsequent sensor data received from the one or more sensor devices.

Abstract: A device may receive, from a consumer device, an application programming interface (API) request that includes information associated with a consumer of data and information associated with a producer of the data. The data may be collected by one or more data sources associated with the producer. The device may identify a consumer context, associated with the consumer, based on the information associated with the consumer. The device may identify a producer context, associated with the producer, based on the information associated with the producer. The device may generate an API response based on the consumer context and the producer context. The API response may include data in accordance with the consumer context and the producer context. The device may provide, to the consumer device, the API response to permit the consumer to view or access the data.