ANALYTICS ENGINES FOR IOT DEVICES

• US 20140244836A1
• Filed: 02/24/2014
• Published: 08/28/2014
• Est. Priority Date: 02/25/2013
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: GOEL, Amit, SHUMAN, Mohammed Ataur Rahman, GUPTA, Binita, AGGARWAL, Ashutosh, SHARMA, Sandeep
• Granted Patent: US 10,257,665 B2
• Time in Patent Office: Days
• US Class Current: 709/224
• CPC Class Codes: H02J 13/00004 characterised by the power network being locally controlled
• CPC Class Codes: H02J 13/00017 using optical fiber
• CPC Class Codes: H02J 13/00028 involving the use of Internet protocols
• CPC Class Codes: H02J 2310/14 The load or loads being home appliances
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: H04L 12/2827 Reporting to a device within the home network; wherein the reception of the information reported automatically triggers the execution of a home appliance functionality
• CPC Class Codes: H04W 4/08 User group management
• CPC Class Codes: H04W 4/70 Services for machine-to-machine communication [M2M] or machine type communication [MTC]
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• CPC Class Codes: Y04S 20/20 End-user application control systems
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/242 Home appliances
• CPC Class Codes: Y04S 20/244 the home appliances being or involving heating ventilating and air conditioning [HVAC] units
• CPC Class Codes: Y04S 20/246 the system involving the remote operation of lamps or lighting equipment
• CPC Class Codes: Y04S 40/124 using wired telecommunication networks or data transmission busses
• CPC Class Codes: Y04S 40/128 involving the use of Internet protocol

Abstract

Methods and apparatuses for optimizing performance using data from an Internet of Things (IoT) device with analytics engines. The method receives, from a requesting Internet of Things (IoT) device, a request for trend data of physical resource consumption based at least in part on a portion of received data from at least one of a plurality of IoT devices. The method retrieves, from memory of an analytics engine, at least the portion of the received data. The method calculates, in a calculator of the analytics engine, the trend data based on at least the portion of the received data. The method transmits, to the requesting IoT device, the calculated trend data, wherein the requesting IoT device adjusts parameters in an IoT device using the calculated trend data.

Claims

1. A method to optimize performance using data from an Internet of Things (IoT) device with analytics engines, the method comprising:

receiving, from a requesting Internet of Things (IoT) device, a request for trend data of physical resource consumption based at least in part on a portion of received data from at least one of a plurality of IoT devices;

retrieving, from memory of an analytics engine, at least the portion of the received data;

calculating, in a calculator of the analytics engine, the trend data based on at least the portion of the received data; and

transmitting, to the requesting IoT device, the calculated trend data, wherein the requesting IoT device adjusts parameters in an IoT device using the calculated trend data.

2. The method of claim 1, wherein data is periodically transmitted from at least one IoT device in a network with the analytics engine to be stored in memory.

3. The method of claim 1, wherein data is transmitted from at least one IoT device in a network with the analytics engine in real time to be stored in memory.

4. The method of claim 1, wherein the request from the requesting IoT device comprises historical data from the requesting IoT device.

5. The method of claim 1, wherein the request from the requesting IoT device comprises historical data from at least one device in a group with the requesting IoT device.

6. The method of claim 1, wherein the requesting IoT device delays adjusting parameters after calculating the trend data.

7. The method of claim 1, wherein the requesting IoT device uses the calculated trend data to adjust parameters in more than one IoT device in a group.

8. The method of claim 1, wherein the request for trend data comprises a request for data associated with a group of IoT devices.

9. The method of claim 1, wherein the memory storing the received data is shared among more than one analytics engine.

10. The method of claim 1, further comprising calculating a prediction based at least in part on the trend data.

11. The method of claim 1, wherein at least one IoT device in a network with the analytics engine transfers to a different group through at least one of the following transitions:

occupancy of location, geographical location, ownership, and operating system.

12. An apparatus comprising:

a processor configured to optimize performance using data from an Internet of Things (IoT) device with analytics engines;

logic configured to receive, from a requesting Internet of Things (IoT) device, a request for trend data of physical resource consumption based at least in part on a portion of received data from at least one of a plurality of IoT devices;

logic configured to retrieve, from memory of an analytics engine, at least the portion of the received data;

logic configured to calculate, in a calculator of the analytics engine, the trend data based on at least the portion of the received data; and

logic configured to transmit, to the requesting IoT device, the calculated trend data, wherein the requesting IoT device adjusts parameters in an IoT device using the calculated trend data.

13. The apparatus of claim 12, wherein data is periodically transmitted from at least one IoT device in a network with the analytics engine device to be stored in memory.

14. The apparatus of claim 12, wherein data is transmitted in real time from at least one IoT device in a network with the analytics engine to be stored in memory.

15. The apparatus of claim 12, wherein the requesting IoT device delays adjusting parameters after calculating the trend data.

16. The apparatus of claim 12, wherein the requesting IoT device uses the calculated trend data to adjust parameters in more than one IoT device in a group.

17. The apparatus of claim 12, wherein the request for trend data comprises a request for data associated with a group of IoT devices.

18. The apparatus of claim 12, wherein the memory storing the received data is shared among more than one analytics engine.

19. The apparatus of claim 12, further comprising calculating a prediction based at least in part on the trend data.

20. An analytics engine comprising:

a receiver to receive, from a requesting Internet of Things (IoT) device, a request for trend data of physical resource consumption based at least in part on a portion of received data from at least one of a plurality of IoT devices;

a data retriever to retrieve, from memory of an analytics engine, at least the portion of the received data;

a calculator to calculate, in a calculator of the analytics engine, the trend data based on at least the portion of the received data; and

a transmitter, to the requesting IoT device, the calculated trend data, wherein the requesting IoT device adjusts parameters in an IoT device using the calculated trend data.

21. The analytics engine of claim 20, wherein data is periodically transmitted from the at least one IoT device to be stored in memory.

22. The analytics engine of claim 20, wherein data is transmitted from the at least one IoT device in real time to be stored in memory.

23. The analytics engine of claim 20, wherein the requesting IoT device delays adjusting parameters after calculating the trend data.

24. The analytics engine of claim 20, wherein the requesting IoT device uses the calculated trend data to adjust parameters in more than one IoT device in a group.

25. The analytics engine of claim 20, wherein the request for trend data comprises a request for data associated with a group of IoT devices.

26. The analytics engine of claim 20, wherein the memory storing the received data is shared among more than one analytics engine.

27. The analytics engine of claim 20, further comprising calculating a prediction based at least in part on the trend data.

28. A non-transitory computer-readable storage medium comprising code, which, when executed by a processor, causes the processor to perform operations for optimizing performance using data from an Internet of Things (IoT) device with analytics engines;

code for receiving, from a requesting Internet of Things (IoT) device, a request for trend data of physical resource consumption based at least in part on a portion of received data from at least one of a plurality of IoT devices;

code for retrieving, from memory of an analytics engine, at least the portion of the received data;

code for calculating, in a calculator of the analytics engine, the trend data based on at least the portion of the received data; and

code for transmitting, to the requesting IoT device, the calculated trend data, wherein the requesting IoT device adjusts parameters in an IoT device using the calculated trend data.

29. The non-transitory computer-readable storage medium of claim 28, further comprising transmitting data periodically to memory.

30. The non-transitory computer-readable storage medium of claim 28, further comprising code for delaying adjusting parameters trend data is calculated.