Contextual IoT with blockchain

1. A computing system comprising:

a network interface configured to receive sensor data comprising time-series measurements captured of an object that is in a multi-party transactional process; and

a processor configured to

correlate the received sensor data with business data from a data store based on a common attribute between the received sensor data and the business data;

dynamically identify a party of the multi-party transactional process that is in possession of the object based on the received sensor data and the correlated business data,

determine that the dynamically identified party is in violation of a predefined constraint of the multi-party transactional process based on a comparison of the received sensor data to one or more rules of the multi-party transactional process, wherein a violation of the predefined constraint occurs when the time-series measurements captured from the object are outside of the conditions defined in the one or more rules of the multi-party transactional process,

generate a data block comprising the time-series measurements of the object, paired with an identifier of the dynamically identified party,

store information about the violation of the predefined constraint within the data block,

store the data block within a blockchain on a distributed ledger, and

transmit an alert to one or more parties of the multi-party transactional process indicating the predefined constraint has been violated.

2. The computing system of claim 1 , wherein the network interface is configured to receive one or more of temperature, vibration, pressure, and geo-location measurements captured of the object at a current position within the multi-party transactional process.

3. The computing system of claim 1 , wherein the processor is further configured to dynamically identify context including one or more of a type of material of the object, a vehicle identifier of a current transport, a party identifier, and an order identifier based on the received sensor data and the correlated business data of the party obtained from the data store, and add the context to the data block before storing the data block on the blockchain.

4. The computing system of claim 1 , wherein the processor is configured to correlate the received sensor data and the business data from the data store based on one or more of time and location within the received sensor data and the business data.

5. The computing system of claim 1 , wherein the processor is configured to dynamically identify a change in possession of the object from one party to another party in the multi-party transactional process based on the received sensor data and the correlated business data of the party obtained from the data store, and record the change in possession in the blockchain on the distributed ledger.

6. The computing system of claim 1 , wherein the object comprises a temperature-controlled object, the sensor data comprise temperature data, and the processor is configured to determine whether a current temperature at the current position of the object satisfies a predetermined temperature constraint based on the received sensor data and the correlated business data of the party obtained from the data store.

7. The computing system of claim 1 , wherein the processor is configured to determine that the object the predefined constraint of the multi-party transactional process, based on a comparison of a temperature value and a duration of time value within the received sensor data in comparison to the one or more rules of the multi-party transactional process.

8. The computing system of claim 1 , wherein the processor is configured to dynamically identify the party of the multi-party transactional process that is in possession of the object based on a point in time of a change in possession between two parties of the multi-party transactional processes identified from the business data in a correlated sales order.

9. A method comprising:

receiving sensor data comprising time-series measurements captured of an object that is in a multi-party transactional process;

correlating the received sensor data with business data from a data store based on a common attribute between the received sensor data and the business data;

dynamically identifying a party of the multi-party transactional process that is in possession of the object based on the received sensor data and the correlated business data;

determining that the dynamically identified party is in violation of a predefined constraint of the multi-party transactional process based on a comparison of the received sensor data to one or more rules of the multi-party transactional process, wherein a violation of the predefined constraint occurs when the time-series measurements captured from the object are outside of the conditions defined in the one or more rules of the multi-party transactional process;

generating a data block comprising the time-series measurements of the object paired with an identifier of the dynamically identified party;

storing information about the violation of the predefined constraint within the data block;

storing the data block within a blockchain on a distributed ledger; and

transmitting an alert to one or more parties of the multi-party transactional process indicating the predefined constraint has been violated.

10. The method of claim 9 , wherein the receiving the sensor data comprises receiving one or more of temperature, vibration, pressure, and geo-location measurement captured of the object at a current position within the multi-party transactional process.

11. The method of claim 9 , wherein the dynamically identifying further comprises identifying context including one or more of a type of material of the object, a vehicle identifier of a current transport, a party identifier, and an order identifier, and adding the context to the data block before storing the data block on the blockchain.

12. The method of claim 9 , wherein the correlating comprises correlating the received sensor data and the business data from the data store based on one or more of time and location within the received sensor data and the business data.

13. The method of claim 9 , wherein the dynamically identifying comprises dynamically identifying a change in possession of the object from one party to another party in the multi-party transactional process based on the received sensor data and the correlated business data of the party obtained from the data store, and recording the change in possession in the blockchain on the distributed ledger.

14. The method of claim 9 , wherein the object comprises a temperature-controlled object, the sensor data comprise temperature data, and the dynamically identifying comprises determining whether a current temperature at the current position of the object satisfies a predetermined temperature constraint based on the received sensor data and the correlated business data of the party obtained from the data store.

15. The method of claim 9 , wherein the determining comprises determining that the object violates the predefined constraint of the multi-party transactional process based on a comparison of a temperature value and a duration of time value within the received sensor data in comparison to the one or more rules of the multi-party transactional process.

16. A non-transitory computer-readable medium storing instructions which when executed by a processor cause a computer to perform:

receiving sensor data comprising time-series measurements captured of an object that is in a multi-party transactional process;

correlating the received sensor data with business data from a data store based on a common attribute between the received sensor data and the business data;

dynamically identifying a party of the multi-party transactional process that is in possession of the object based on the received sensor data and the correlated business data;

determining that the dynamically identified party is in violation of a predefined constraint of the multi-party transactional process based on a comparison of the received sensor data to one or more rules of the multi-party transactional process, wherein a violation of the predefined constraint occurs when the time-series measurements captured from the object are outside of the conditions defined in the one or more rules of the multi-party transactional process;

generating a data block comprising the time-series measurements of the object paired with an identifier of the dynamically identified party;

storing information about the violation of the predefined constraint within the data block;

storing the data block within a blockchain on a distributed ledger; and

transmitting an alert to one or more parties of the multi-party transactional process indicating the predefined constraint has been violated.

17. The non-transitory computer-readable medium of claim 16 , wherein the receiving the sensor data comprises receiving one or more of temperature, vibration, pressure, and geo-location measurements captured of the object at a current position within the multi-party transactional process.

18. The non-transitory computer-readable medium of claim 16 , wherein the dynamically identifying further comprises identifying context including one or more of a type of material of the object, a vehicle identifier of a current transport, a party identifier, and an order identifier based on the received sensor data and the correlated business data of the party obtained from the data store, and adding the context to the data block before storing the data block on the blockchain.

19. The non-transitory computer-readable medium of claim 16 , wherein the correlating comprises correlating the received sensor data and the business data from the data store based on one or more of time and location attributes within the received sensor data and the business data.