Patent Publication Number: US-2023152104-A1

Title: Methods and apparatuses for implementing integrated image sensors

Description:
TECHNICAL FIELD 
     Aspects of the present disclosure relate to implementing integrated image sensors for traffic control and monitoring. 
     BACKGROUND 
     In some environments, vehicle and pedestrian traffic may cause obstructions in a transportation infrastructure. For example, traffic collisions, road constructions, and/or broken down vehicles may cause such traffic obstructions. While emergency personnel may assist in reducing the obstructions (e.g., police redirecting traffic), such countermeasures may be labor intensive. Further, when traffic obstructions build up on one road, other roads may experience obstructions as vehicles get blocked or diverted. Therefore, improvements may be desirable. 
     SUMMARY 
     This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the DETAILED DESCRIPTION. This summary is not intended to identify key features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. 
     Aspects of the present disclosure include methods, systems, and non-transitory computer readable media for receiving a plurality of images of a plurality of street locations from a plurality of image capturing devices, identifying an event at a street location of the plurality of street locations based on one or more of the plurality of images, determining at least one new route for at least one vehicle based on the event and one or more of the plurality of images, and transmitting at least one indication indicating the at least one new route to at least one receiving device. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The features believed to be characteristic of aspects of the disclosure are set forth in the appended claims. In the description that follows, like parts are marked throughout the specification and drawings with the same numerals, respectively. The drawing figures are not necessarily drawn to scale and certain figures may be shown in exaggerated or generalized form in the interest of clarity and conciseness. The disclosure itself, however, as well as a preferred mode of use, further objects and advantages thereof, will be best understood by reference to the following detailed description of illustrative aspects of the disclosure when read in conjunction with the accompanying drawings, wherein: 
         FIG.  1    illustrates an example of an environment for implementing integrated image sensors for traffic monitoring and control in accordance with aspects of the present disclosure; 
         FIG.  2    illustrates an example method for implementing integrated image sensors for traffic monitoring and control in accordance with aspects of the present disclosure; and 
         FIG.  3    illustrates an example of a computer system in accordance with aspects of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     The following includes definitions of selected terms employed herein. The definitions include various examples and/or forms of components that fall within the scope of a term and that may be used for implementation. The examples are not intended to be limiting. 
     Aspects of the present disclosure may include a system that monitors and controls traffic via a controller and cameras. The system detects an event (such as a traffic collision, stalled vehicle, construction, etc.) based on the images captured by the cameras, and reroutes traffic around and/or away from the event. For example, the system may control traffic lights to reroute the traffic by changing the light patterns (e.g., extending the green light to allow vehicles to reroute around the event). The system may direct emergency vehicles toward the event to assist with any injuries, hazards, etc. In some aspects, the system may detect suspect vehicles (e.g., vehicles used in child abduction) based on the images captured by the cameras. In some instances, the controller may be integrated into one or more of the cameras. 
     Referring to  FIG.  1   , in an aspect of the present disclosure, an example of an environment  100  for monitoring and/or controlling traffic is shown according to aspects of the present disclosure. The environment  100  may include a controller  102  configured to monitor and/or control traffic. The environment  100  may include image capturing devices  104   a - f  configured to capture images and/or videos of street locations. The image capturing devices  104   a - f  may include cameras, video recorders, etc. The image capturing devices  104   a - f  may be deployed at intersections or other locations along or near streets. The controller  102  may include a processor  140  that executes instructions stored in a memory  150  for performing the functions described herein. 
     The term “processor,” as used herein, can refer to a device that processes signals and performs general computing and arithmetic functions. Signals processed by the processor can include digital signals, data signals, computer instructions, processor instructions, messages, a bit, a bit stream, or other computing that can be received, transmitted and/or detected. A processor, for example, can include microprocessors, controllers, digital signal processors (DSPs), field programmable gate arrays (FPGAs), programmable logic devices (PLDs), state machines, gated logic, discrete hardware circuits, and other suitable hardware configured to perform the various functionality described herein. 
     In some aspects, the controller  102  may include memory  150 . The memory  150  may include software instructions and/or hardware instructions. The processor  140  may execute the instructions to implement aspects of the present disclosure. 
     The term “memory,” as used herein, can include volatile memory and/or nonvolatile memory. Non-volatile memory can include, for example, ROM (read only memory), PROM (programmable read only memory), EPROM (erasable PROM) and EEPROM (electrically erasable PROM). Volatile memory can include, for example, RAM (random access memory), synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), and direct RAM bus RAM (DRRAM). 
     In certain aspects, the processor  140  may include a communication component  142  configured to communicate with the image capturing devices  104   a - f  and/or other external devices (not shown). The processor  140  may include an artificial intelligence (AI) component  144  configured to analyze captured images and/or determine routes based on the captured images. 
     During operation, in certain aspects, the image capturing devices  104   a - f  may be deployed along street locations being monitored by the image capturing devices  104   a - f . For example, the image capturing devices  104   a - f  may be deployed on traffic lights, street lamps, buildings, or other suitable infrastructures. The image capturing devices  104   a - f  may capture images  106  of the street locations. The images  106  may be still images and/or videos. The image capturing devices  104   a - f  may transmit the captured images  106  to the controller  102  via communication channels  110   a - f . The communication channels  110   a - f  may be wired and/or wireless communication links. 
     In some aspects, the communication component  142  of the controller  102  may receive the images  106  captured by the image capturing devices  104   a - f . The AI component  144  of the controller  102  may analyze the images  106  to identify one or more events occurring in the street locations. The AI component  144  may be implemented using one or more of machine learning algorithms, convoluted neural networks, or other suitable mechanisms to monitor and/or control traffic according to aspects of the present disclosure. Examples of events may include one or more of a traffic collision, a road construction, a traffic congestion, an injured person, a hazard, and/or a broken-down vehicle. Based on the identified one or more events and/or the images  106 , the AI component  144  of the controller  102  may generate one or more new routes for one or more vehicles at the street locations. The one or more new routes may direct the one or more vehicles away, around, or toward the events. The communication component  142  of the controller  102  may transmit the one or more new routes to a receiving device for indicating to the one or more vehicles. For example, the communication component  142  may transmit indications to traffic lights to change light patterns (e.g., activating, deactivating, and/or extending certain traffic lights). 
     In a first example, the controller  102  may receive the images  106  from the image capturing devices  104   a - f  via the communication channels  110   a - f . Based on the images  106 , the AI component  144  may identify an event  130 , such as a traffic collision. The AI component  144  may identify a vehicle  120  (e.g., a non-emergency service vehicle) heading toward the event  130 . In response, the AI component  144  may determine a first route  124  that indicates a path leading the vehicle  120  away and/or around the event  130 . The first route  124  may indicate a path that leads non-emergency service vehicles away from the event  130  to reduce and/or clear traffic congestion at or near (e.g., within 5 meters, 10 meters, 20 meters, or 50 meters) the event  130 . The communication component  142  of the controller  102  may transmit an indication indicating the first route  124  to one or more traffic lights (not shown) to direct the vehicle  120  along the first route  124 . The indication indicating the first route  124  may include light patterns for the one or more traffic lights to implement the first route  124 . The indication indicating the first route  124  may include global positioning system coordinates of an origin and/or a destination. The indication indicating the first route  124  may include a list of directions to traverse the first route  124 . 
     In alternative implementations, the communication component  142  may transmit an indication indicating the first route  124  to a first traffic light. The first traffic light may relate the indication to a second traffic light, and so forth and so on. 
     In a second example, the controller  102  may receive the images  106  from the image capturing devices  104   a - f  via the communication channels  110   a - f . Based on the images  106 , the AI component  144  may identify an event  130 , such as a pedestrian struck by a vehicle. The AI component  144  may identify an emergency service vehicle  122  (e.g., such as an ambulance) summoned for the event  130 . In response, the AI component  144  may determine a second route  126  that indicates a path leading the emergency service vehicle  122  toward the event  130 . The second route  126  may assist a driver of the emergency service vehicle  122  to locate and/or reach the event  130 . The communication component  142  of the controller  102  may transmit an indication signal indicating the second route  126  to a global positioning system (GPS) in the emergency service vehicle  122  to direct the driver of the emergency service vehicle  122  to the event  130 . 
     In a third example, the controller  102  may receive the images  106  from the image capturing devices  104   a - f  via the communication channels  110   a - f . The controller  102  may receive a vehicle identification (e.g., a make, a model, a license plate number, etc.) of a suspect vehicle associated with a potential kidnapping and/or a missing person. Based on the images  106 , the AI component  144  may identify an event  130 , such as the suspect vehicle. Further, the AI component  144  may identify an emergency service vehicle  122  (e.g., law enforcement vehicle) searching for the kidnapped victim and/or the missing person. In response, the AI component  144  may determine a second route  126  that indicates a path leading the emergency service vehicle  122  toward the event  130 . The second route  126  may assist a driver (e.g., law enforcement officer) of the emergency service vehicle  122  to locate and/or reach the event  130 . The communication component  142  of the controller  102  may transmit an indication signal indicating the second route  126  to an onboard computer in the emergency service vehicle  122  to direct the driver of the emergency service vehicle  122  to the event  130 . Additionally or alternative, the communication component  142  may transmit an notification to the onboard computer including the second route  126 , the vehicle description of the suspect vehicle, a victim description, etc. 
     In some aspects of the present disclosure, the controller  102  and/or the AI component  144  may include image recognition algorithms to perform license plate recognition, vehicle identification, and/or facial recognition. 
     Turning to  FIG.  2   , an example of a method  200  for monitoring and/or controlling traffic may be implemented by the controller  102 , the image capturing devices  104   a - f , the processor  140 , the communication component  142 , the AI component  144 , and/or the memory  150 . One or more of the controller  102 , the image capturing devices  104   a - f , the processor  140 , the communication component  142 , the AI component  144 , and/or the memory  150  may be configured to or provide means for implementing aspects of the method  200 . 
     At block  202 , the method  200  may receive a plurality of images of a plurality of street locations from a plurality of image capturing devices. The controller  102 , the image capturing devices  104   a - f , the processor  140 , the communication component  142 , and/or the memory  150  may be configured to or provide means for receiving a plurality of images of a plurality of street locations from a plurality of image capturing devices. 
     At block  204 , the method  200  may identify an event at a street location of the plurality of street locations based on one or more of the plurality of images. The controller  102 , the AI component  144 , and/or the memory  150  may be configured to or provide means for identifying an event at a street location of the plurality of street locations based on one or more of the plurality of images. 
     At block  206 , the method  200  may determine at least one new route for at least one vehicle based on the event and one or more of the plurality of images. The controller  102 , the AI component  144 , and/or the memory  150  may be configured to or provide means for determining at least one new route for at least one vehicle based on the event and one or more of the plurality of images. 
     At block  208 , the method  200  may transmit at least one indication indicating the at least one new route to at least one receiving device. The controller  102 , the processor  140 , the communication component  142 , and/or the memory  150  may be configured to or provide means for transmitting at least one indication indicating the at least one new route to at least one receiving device. 
     Aspects of the present disclosure includes the method above, wherein the event includes one or more of a traffic collision, a road construction, a traffic congestion, an injured person, a hazard, and/or a broken-down vehicle. 
     Aspects of the present disclosure includes any of the methods above, wherein the at least one new route indicates a path leading the at least one vehicle around or away from the event. 
     Aspects of the present disclosure includes any of the methods above, wherein transmitting the at least one indication comprises transmitting a plurality of signals to a plurality of traffic lights to direct the at least one vehicle around or away from the event. The controller  102 , the processor  140 , the communication component  142 , and/or the memory  150  may be configured to or provide means for transmitting the at least one indication. 
     Aspects of the present disclosure includes any of the methods above, further comprising identifying an emergency vehicle based on at least an image of the plurality of images, wherein the at least one new route indicates a path leading the emergency vehicle toward the event. The controller  102 , the AI component  144 , and/or the memory  150  may be configured to or provide means for identifying the emergency vehicle. 
     Aspects of the present disclosure includes any of the methods above, further comprising receiving a suspect vehicle identification of a suspect vehicle associated one or more of a kidnapping or a missing person alert, wherein identifying the event includes identifying the suspect vehicle based on the suspect vehicle identification identified in the one or more of the plurality of images. The controller  102 , the processor  140 , the communication component  142 , the AI component  144 , and/or the memory  150  may be configured to or provide means for receiving the suspect vehicle identification and/or identifying the suspect vehicle. 
     Aspects of the present disclosure includes any of the methods above, further comprising notifying a law enforcement agency. 
     Aspects of the present disclosure includes any of the methods above, further comprising identifying an emergency vehicle based on at least an image of the plurality of images, wherein the at least one new route indicates a path leading the emergency vehicle toward the event. The controller  102 , the processor  140 , the AI component  144 , and/or the memory  150  may be configured to or provide means for identifying the emergency vehicle. 
     Aspects of the present disclosures may be implemented using hardware, software, or a combination thereof and may be implemented in one or more computer systems or other processing systems. In an aspect of the present disclosures, features are directed toward one or more computer systems capable of carrying out the functionality described herein. An example of such the computer system  300  is shown in  FIG.  3   . In some examples, the controller  102  and/or the image capturing devices  104   a - f  may be implemented as the computer system  300  shown in  FIG.  3   . The controller  102  and/or the image capturing devices  104   a - f  may include some or all of the components of the computer system  300 . 
     The computer system  300  includes one or more processors, such as processor  304 . The processor  304  is connected with a communication infrastructure  306  (e.g., a communications bus, cross-over bar, or network). Various software aspects are described in terms of this example computer system. After reading this description, it will become apparent to a person skilled in the relevant art(s) how to implement aspects of the disclosures using other computer systems and/or architectures. 
     The computer system  300  may include a display interface  302  that forwards graphics, text, and other data from the communication infrastructure  306  (or from a frame buffer not shown) for display on a display unit  330 . Computer system  300  also includes a main memory  308 , preferably random access memory (RAM), and may also include a secondary memory  310 . The secondary memory  310  may include, for example, a hard disk drive  312 , and/or a removable storage drive  314 , representing a floppy disk drive, a magnetic tape drive, an optical disk drive, a universal serial bus (USB) flash drive, etc. The removable storage drive  314  reads from and/or writes to a removable storage unit  318  in a well-known manner. Removable storage unit  318  represents a floppy disk, magnetic tape, optical disk, USB flash drive etc., which is read by and written to removable storage drive  314 . As will be appreciated, the removable storage unit  318  includes a computer usable storage medium having stored therein computer software and/or data. In some examples, one or more of the main memory  308 , the secondary memory  310 , the removable storage unit  318 , and/or the removable storage unit  322  may be a non-transitory memory. 
     Alternative aspects of the present disclosures may include secondary memory  310  and may include other similar devices for allowing computer programs or other instructions to be loaded into computer system  300 . Such devices may include, for example, a removable storage unit  322  and an interface  320 . Examples of such may include a program cartridge and cartridge interface (such as that found in video game devices), a removable memory chip (such as an erasable programmable read only memory (EPROM), or programmable read only memory (PROM)) and associated socket, and the removable storage unit  322  and the interface  320 , which allow software and data to be transferred from the removable storage unit  322  to computer system  300 . 
     Computer system  300  may also include a communications circuit  324 . The communications circuit  324  may allow software and data to be transferred between computer system  300  and external devices. Examples of the communications circuit  324  may include a modem, a network interface (such as an Ethernet card), a communications port, a Personal Computer Memory Card International Association (PCMCIA) slot and card, etc. Software and data transferred via the communications circuit  324  are in the form of signals  328 , which may be electronic, electromagnetic, optical or other signals capable of being received by the communications circuit  324 . These signals  328  are provided to the communications circuit  324  via a communications path (e.g., channel)  326 . This path  326  carries signals  328  and may be implemented using wire or cable, fiber optics, a telephone line, a cellular link, an RF link and/or other communications channels. In this document, the terms “computer program medium” and “computer usable medium” are used to refer generally to media such as the removable storage unit  318 , a hard disk installed in hard disk drive  312 , and signals  328 . These computer program products provide software to the computer system  300 . Aspects of the present disclosures are directed to such computer program products. 
     Computer programs (also referred to as computer control logic) are stored in main memory  308  and/or secondary memory  310 . Computer programs may also be received via communications circuit  324 . Such computer programs, when executed, enable the computer system  300  to perform the features in accordance with aspects of the present disclosures, as discussed herein. In particular, the computer programs, when executed, enable the processor  304  to perform the features in accordance with aspects of the present disclosures. Accordingly, such computer programs represent controllers of the computer system  300 . 
     In an aspect of the present disclosures where the method is implemented using software, the software may be stored in a computer program product and loaded into computer system  300  using removable storage drive  314 , hard disk drive  312 , or the interface  320 . The control logic (software), when executed by the processor  304 , causes the processor  304  to perform the functions described herein. In another aspect of the present disclosures, the system is implemented primarily in hardware using, for example, hardware components, such as application specific integrated circuits (ASICs). Implementation of the hardware state machine so as to perform the functions described herein will be apparent to persons skilled in the relevant art(s). 
     It will be appreciated that various implementations of the above-disclosed and other features and functions, or alternatives or varieties thereof, may be desirably combined into many other different systems or applications. Also that various presently unforeseen or unanticipated alternatives, modifications, variations, or improvements therein may be subsequently made by those skilled in the art which are also intended to be encompassed by the following claims.