Autonomous data machines and systems

• US 9,910,436 B1
• Filed: 06/25/2015
• Issued: 03/06/2018
• Est. Priority Date: 01/17/2014
• Status: Active Grant

• Current Assignee: Knightscope, Inc.
• Original Assignee: Knightscope, Inc.
• Inventors: Li, William Santana, Stephens, Stacy Dean, Soria-Li, Mercedes, Lehnhardt, Aaron J., Villa, Dominic A., Wong, Phillip, Stoschek, Arne
• Primary Examiner(s): Elchanti, Hussein A.
• Application Number:
  US14/751,115
• Time in Patent Office: 985 Days
• Field of Search: 701 22
• CPC Class Codes: B60L 50/60 using power supplied by batteries in combination with fuel cells B60L50/75
• CPC Class Codes: B60Q 5/005 automatically actuated
• CPC Class Codes: B60W 40/02 related to ambient conditions
• CPC Class Codes: G05D 1/021 specially adapted to land vehicles
• CPC Class Codes: G05D 1/0297 by controlling means in a control room
• CPC Class Codes: G08B 13/00 Burglar, theft or intruder alarms
• CPC Class Codes: G08B 25/10 using wireless transmission systems G08B25/009 takes precedence
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y10S 901/01 Mobile robot

Abstract

Autonomous data machines and systems may be provided, which may be deployed in an environment. The machines may roam within the environment and collect data with aid of one or more sensors. The data may be sent to a control center, which may optionally receive information from additional data sources, such as other on-site sensors, existing static data, or real-time social data. The control center may send instructions to the machines to perform one or more reaction based on the received information. The autonomous data machines may be capable of reacting autonomously to one or more detected condition. In some instances, the autonomous data machines may be employed for security or surveillance.

Claims

1. A system for controlling a plurality of autonomous data machines configured to perform surveillance and monitor security within a predefined location, the system comprising:

a control center in remote communication with the plurality of autonomous data machines, wherein the control center comprises one or more processors located remotely from the plurality of autonomous data machines and are individually or collectively configured to;

receive data indicative of at least one security event occurring at the predefined location, wherein at least a portion of the data is from a plurality of sensors on-board the plurality of autonomous data machines, wherein the predefined location is defined by a plurality of geofences, and wherein at least a portion of the plurality of autonomous data machines are configured to operate within at least one of the plurality of geofences in a concerted manner to identify and react to the at least one security event;

analyze the data to generate a set of instructions for responding to the at least one security event; and

provide the set of instructions to the plurality of autonomous data machines, wherein a plurality of processors on the plurality of autonomous data machines are individually or collectively configured to execute the set of instructions, thereby causing the plurality of autonomous data machines to react in a coordinated manner that maintains performance of surveillance and security monitoring in the predefined location.

2. The system of claim 1, wherein at least a portion of the data comprises information obtained from an online data source external to the plurality of autonomous data machines.

3. The system of claim 1, wherein the security event occurs in the predefined location external to the plurality of autonomous data machines and comprises at least one of the following:

(i) a crime, (ii) a potential criminal activity, (iii) an accident, or (iv) an emergency.

4. The system of claim 1, wherein the data is further indicative of an operational state of the plurality of autonomous data machines, wherein the operational state of the plurality of autonomous data machines is associated with at least one of the following:

(i) an operational health, (ii) a location, (iii) a range of travel, (iv) a state of charge, or (v) a state of abuse, of the plurality of autonomous data machines.

5. The system of claim 1, wherein the one or more processors in the control center are configured to generate and provide the set of instructions to the plurality of autonomous data machines without any human intervention.

6. The system of claim 1, wherein the set of instructions are executed to:

(i) navigation of the plurality of autonomous data machines to a location where the security event is occurring and (ii) at least one of the following;

transmission of information about the security event, generation of audible sounds, collection of a predefined data type, or communication of the predefined data type to one or more other devices or third parties.

7. The system of claim 1, wherein the plurality of autonomous data machines are configured to transmit the data collected by the plurality of sensors to the system according to a pre-determined schedule.

8. The system of claim 2, wherein the data indicative of at least one security event occurring in the predefined location is updated substantially in real-time as the data is being collected using the plurality of sensors and/or obtained from the online data source.

9. The system of claim 1, wherein the plurality of sensors comprise (i) an image sensor and (ii) at least one of the following:

an audio sensor, a thermal sensor, an infrared sensor, a proximity sensor, a motion sensor, or a position sensor.

10. The system of claim 1, wherein the data is also collected using at least one sensor located onsite within the predefined location, and wherein the at least one sensor is remote from the plurality of autonomous data machines.

11. The system of claim 4, wherein the plurality of autonomous data machines are configured to locate and move to a nearest charging station for charging based on the set of instructions when the operational state is indicative of a low state of charge.

12. The system of claim 1, wherein the data indicative of at least one security event occurring in the predefined location comprises data obtained from (i) the plurality of sensors on-board the plurality of autonomous data machines and (ii) at least one of the following:

a-priori knowledge and public data sources.

13. The system of claim 1, wherein at least one of the plurality of geofences is dynamically generated.

14. The system of claim 1, wherein each geofence of the plurality of geofences has at least one of the plurality of autonomous data machines deployed therewithin.

15. The system of claim 1, wherein the data comprises location of a mobile device detected by at least one of the sensors configured to detect a wireless signal of the mobile device.

16. The system of claim 15, wherein the wireless signal is used to create a map of items that may not be visually discernable.

17. The system of claim 15, wherein the location of the mobile device is determined using a specific signature of the wireless signature.

18. The system of claim 1, wherein each of the plurality of autonomous data machines roams freely in any direction in the predetermined location.

19. The system of claim 1, wherein the set of instructions are executed by the plurality of autonomous data machines to cause at least one of the autonomous data machines to alter its travel path to accommodate at least another autonomous data machine that is in charging.

20. A method for controlling a plurality of autonomous data machines configured to perform surveillance and monitor security within a predefined location, the method comprising:

with aid of one or more processors located remotely from the plurality of autonomous data machines individually or collectively;

receiving data indicative of at least one security event occurring in the predefined location, wherein at least a portion of the data is from one or more sensors on-board the plurality of autonomous data machines, wherein the predefined location is defined by a plurality of geofences, and wherein at least a portion of the plurality of autonomous data machines are configured to operate within at least one of the plurality of geofences in a concerted manner to identify and react to the at least one security event;

analyzing the data to generate a set of instructions for responding to the at least one security event; and

providing the set of instructions to the plurality of autonomous data machines, wherein a plurality of processors on the plurality of autonomous data machines are individually or collectively configured to execute the set of instructions, thereby causing the plurality of autonomous data machines to react in a coordinated manner that maintains performance of surveillance and security monitoring in the predefined location.

21. A non-transitory computer readable medium storing instructions that, when executed by one or more processors located remotely from the plurality of autonomous data machines, causes the one or more processors to individually or collectively perform a method for controlling plurality of autonomous data machines configured to perform surveillance and monitor security within a predefined location, the method comprising:

receiving data indicative of at least one security event occurring at the predefined location, wherein at least a portion of the data is from one or more sensors on-board the plurality of autonomous data machines, wherein the predefined location is defined by a plurality of geofences, and wherein at least a portion of the plurality of autonomous data machines are configured to operate within at least one of the plurality of geofences in a concerted manner to identify and react to the at least one security event;

analyzing the data to generate a set of instructions for responding to the at least one security event; and

providing the set of instructions to the plurality of autonomous data machines, wherein a plurality of processors on the plurality of autonomous data machines are individually or collectively configured to execute the set of instructions, thereby causing the plurality of autonomous data machines to react in a coordinated manner that maintains performance of surveillance and security monitoring in the predefined location.