Synaptic neural network core based sensor system

• US 9,881,253 B2
• Filed: 11/07/2014
• Issued: 01/30/2018
• Est. Priority Date: 11/07/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Adams, Samuel S., Belluomini, Wendy A., Friedlander, Robert R., Kraemer, James R.
• Primary Examiner(s): Chaki, Kakali
• Assistant Examiner(s): Nilsson, Eric
• Application Number:
  US14/535,779
• Publication Number:
  US 20160132766A1
• Time in Patent Office: 1,180 Days
• Field of Search: None
• CPC Class Codes: G06F 1/26 Power supply means, e.g. regulation thereof for memories G11C
• CPC Class Codes: G06N 3/049 Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
• CPC Class Codes: G06N 3/063 using electronic means

Abstract

A sensor system comprises: an energy storage device; an intermittent energy release device electrically coupled to the energy storage device, wherein the intermittent energy release device causes the energy storage device to release stored energy intermittently; a sensor electrically coupled to the energy storage device; a register electrically coupled to the sensor, wherein the register stores readings from the sensor; a synaptic neural network core electrically coupled to the sensor, wherein the synaptic neural network core converts the readings from the sensor into a synthetic context-based object that is derived from the readings and a context object; a transponder electrically coupled to the synaptic neural network core; and a storage buffer within the transponder, wherein the storage buffer stores the synthetic context-based object for transmission by the transponder to a monitoring system.

Claims

1. A sensor system comprising:

an energy storage device;

an intermittent energy release device electrically coupled to the energy storage device, wherein the intermittent energy release device causes the energy storage device to release stored energy intermittently;

a sensor electrically coupled to the energy storage device, wherein the sensor detects physical events occurring at a physical device, and wherein the sensor is intermittently powered by electrical energy received from the energy storage device via the intermittent energy release device;

a synaptic neural network core electrically coupled to the sensor, wherein the synaptic neural network core converts sensor readings from the sensor into a synthetic context-based object that is derived from the sensor readings and a context object, and wherein the synthetic context-based object describes the physical events occurring at the physical device;

a transponder electrically coupled to the synaptic neural network core; and

a storage buffer within the transponder, wherein the storage buffer stores the synthetic context-based object for transmission by the transponder to a monitoring system.

2. The sensor system of claim 1, further comprising:

a register electrically coupled to the sensor, wherein the register stores the sensor readings from the sensor.

3. The sensor system of claim 1, further comprising:

synaptic connections that electrically connect electronic neurons within the synaptic neural network core, wherein the synaptic connections convert the sensor readings from the sensor into a non-contextual data object that is used, with the context object, to generate the synthetic context-based object.

4. The sensor system of claim 1, further comprising:

an ambient power collection device coupled to the energy storage device, wherein the ambient power collection device converts ambient forces into electricity.

5. The sensor system of claim 4, wherein the ambient forces are from a group consisting of radio frequency energy, heat, electrical induction forces, acceleration forces, and vibration.

6. The sensor system of claim 1, wherein the intermittent energy release device comprises a breakdown diode.

7. The sensor system of claim 1, further comprising:

a sensor identification register, wherein the sensor identification register stores an identifier of the sensor as the context object;

a set of one or more excitatory sensing units within the sensor, wherein excitatory sensing units produce a first type of signal in response to sensing a first type of physical event associated with a physical condition, and wherein the first type of signal is transmitted on a first type of electronic neuron;

a set of one or more inhibitory sensing units within the sensor, wherein inhibitory sensing units produce a second type of signal in response to sensing a second type of physical event associated with the physical condition, and wherein the second type of signal is transmitted on a second type of electronic neuron;

a set of synaptic connections within the synaptic neural network core that selectively couple the first type of electronic neuron and the second type of electronic neuron to a non-contextual object register, wherein the non-contextual object register stores non-contextual data received from the set of synaptic connections; and

a synthetic event synaptic neural network core electrically coupled to a synthetic event descriptor register and the sensor identification register, wherein the synthetic event synaptic neural network core generates a synthetic event descriptor from contents of the non-contextual object register and the sensor identification register.

8. The sensor system of claim 1, further comprising:

a resistor that electrically couples the intermittent energy release device to the sensor, wherein the resistor is sized to allow electrical power to be transmitted to the sensor for a predetermined amount of time.

9. A method of optimizing sensor operations, the method comprising:

storing electrical energy on an energy storage device;

intermittently releasing stored electrical energy from the energy storage device to a sensor, wherein intermittently released stored electrical energy from the energy storage device activates one or more sensing units in the sensor, wherein the sensor detects physical events occurring at a physical device, and wherein the sensor is intermittently powered by electrical energy received from the energy storage device via the intermittent energy release device;

capturing sensor readings by the one or more sensing units in the sensor;

transmitting the sensor readings to a register for storage;

loading the sensor readings from the register onto a synaptic neural network core;

converting, by the synaptic neural network core, the sensor readings into a synthetic event identifier, wherein the synthetic event identifier is generated from the sensor readings and a context object, and wherein the synthetic event identifier describes the physical events occurring at the physical device;

loading the synthetic event identifier onto a register on a transponder device; and

transmitting the synthetic event identifier from the transponder device to a monitoring system.

10. The method of claim 9, wherein the context object is an identifier of a sensor type for the sensor.

11. The method of claim 9, further comprising:

generating power from ambient forces, wherein the power is generated by an ambient power collection device that is coupled to the energy storage device, wherein the ambient power collection device converts ambient forces into electricity, and wherein the ambient forces are from a group consisting of radiofrequency energy, heat, electrical induction forces, acceleration forces, and vibration.

12. The method of claim 9, wherein the intermittent energy release device comprises a breakdown diode.

13. The method of claim 9, further comprising:

storing, on a sensor identification register, an identifier of a sensor type for the sensor as the context object;

producing, by a set of one or more excitatory sensing units within the sensor, a first type of signal in response to sensing a first type of physical event associated with a physical condition, and wherein the first type of signal is transmitted on a first type of electronic neuron;

producing, by a set of one or more inhibitory sensing units within the sensor, a second type of signal in response to sensing a second type of physical event associated with the physical condition, wherein the second type of signal is transmitted on a second type of electronic neuron;

selectively coupling, by a set of synaptic connections within the synaptic neural network core, the first type of electronic neuron and the second type of electronic neuron to a non-contextual object register, and wherein the non-contextual object register stores non-contextual data received from the set of synaptic connections; and

generating, by a synthetic event synaptic neural network core that is electrically coupled to a synthetic event descriptor register and the sensor identification register, a synthetic event descriptor from contents of the non-contextual object register and the sensor identification register.

18. The method of claim 9, wherein the energy stored on the energy storage device is from an ambient power collection device that generates electricity from ambient vibrations on a bridge, wherein an amount of electricity generated by the ambient power collection device is proportional to a level of the ambient vibrations on the bridge, wherein the sensor comprises multiple vibration detectors that detect the ambient vibrations, wherein the multiple vibration detectors are part of a sensor system, wherein the multiple vibration detectors are mounted on the bridge, and wherein the method further comprises:

powering up, from electricity generated by the ambient power collection device, a quantity of the multiple vibration detectors in proportion to the electricity generated by the ambient power collection device, wherein the quantity of the multiple vibration detectors that are powered up is proportional to an amount of electricity generated by the ambient power collection device; and

determining, by the sensor system, a level of vehicular traffic on the bridge based on the quantity of the multiple vibration detectors that are powered up by the electricity generated by the ambient power collection device.

20. The method of claim 9, wherein the sensor is part of a sensor system, wherein the synaptic neural network core is in the sensor system, and wherein the method further comprises:

receiving, by an antenna in the sensor system, a radio frequency (RF) signal from a monitoring system, wherein the RF signal includes RF energy and instructions;

powering the sensor with the RF energy in the RF signal; and

executing, by the synaptic neural network core in the sensor system, the instructions in the RF signal in order to convert the sensor readings from the sensor into the synthetic event identifier.

14. A sensor system comprising:

an energy storage device;

an intermittent energy release device electrically coupled to the energy storage device, wherein the intermittent energy release device causes the energy storage device to release stored energy intermittently to a sensor that detects physical events occurring at a physical device;

a synaptic neural network core electrically coupled to the intermittent energy release device, wherein the synaptic neural network core converts sensor readings directly received from the sensor into a synthetic context-based object that is derived from the sensor readings and a context object, and wherein the synthetic context-based object describes the physical events occurring at the physical device;

a transponder electrically coupled to the synaptic neural network core; and

a storage buffer within the transponder, wherein the storage buffer stores the synthetic context-based object for transmission by the transponder to a monitoring system.

15. The sensor system of claim 14, further comprising:

an ambient power collection device coupled to the energy storage device, wherein the ambient power collection device converts ambient forces into electricity.

16. The sensor system of claim 15, wherein the ambient forces are from a group consisting of radiofrequency energy, heat, electrical induction forces, acceleration forces, and vibration.

17. The sensor system of claim 14, wherein the intermittent energy release device comprises a breakdown diode.

19. The sensor system of claim 14, further comprising:

a sensor identification register, wherein the sensor identification register stores an identifier of the sensor as the context object;

a set of one or more excitatory sensing units within the sensor, wherein excitatory sensing units produce a first type of signal in response to sensing a first type of physical event associated with a physical condition, and wherein the first type of signal is transmitted on a first type of electronic neuron;

a set of one or more inhibitory sensing units within the sensor, wherein inhibitory sensing units produce a second type of signal in response to sensing a second type of physical event associated with the physical condition, and wherein the second type of signal is transmitted on a second type of electronic neuron;

a set of synaptic connections within the synaptic neural network core that selectively couple the first type of electronic neuron and the second type of electronic neuron to a non-contextual object register, wherein the non-contextual object register stores non-contextual data received from the set of synaptic connections; and

a synthetic event synaptic neural network core electrically coupled to a synthetic event descriptor register and the sensor identification register, wherein the synthetic event synaptic neural network core generates a synthetic event descriptor from contents of the non-contextual object register and the sensor identification register.