DESC:TECHNICAL FIELD
[0001] The present disclosure relates, in general, to capturing digital and thermal images and measuring body temperature of entities. In particular, the present disclosure relates to a means to monitor temperature of a group of entities.

BACKGROUND
[0002] Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] COVID 19 has affected the world in an unprecedented fashion. In order to avoid spread of this disease such as this, many preventive measures are being taken all over the world. One of the preventive measures is to screen people based on body temperature and providing early treatment to those having higher body temperature (fever). Further, identifying, and quarantining people with these types of symptoms helps in restricting the spread of the disease. The traditional methods of body temperature measurement are slow (time consuming) and typically measure temperature for one entity at a time.
[0004] There is, therefore, a requirement in the art for a means to measure temperature accurately of more than one entity at a time.

OBJECTS OF THE PRESENT DISCLOSURE
[0005] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0006] It is an object of the present disclosure to provide systems and methods to measure body temperature of multiple entities at an instance.
[0007] It is an object of the present disclosure to provide systems and methods to capture optical and thermal images of the entities and determine body temperature of the entities.
[0008] It is another object of the present disclosure to provide systems and methods to provide a contact less mechanism for measuring body temperature of multiple entities present in within a field of view of the camera device.

SUMMARY
[0009] The present disclosure relates, in general, to capturing digital and thermal images and measuring body temperature of entities. In particular, the present disclosure relates to a means to monitor temperature of a group of entities.
[0010] An aspect of the present disclosure provides a method for determining body temperature of a plurality of entities at an instance, said method comprising: receiving, at a processor of a computing device, a plurality of optical images and a plurality of thermal images corresponding to each of an entity of the plurality of entities, the plurality of optical images being captured using an optical image capturing device and the plurality of thermal images being captured using a thermal image capturing device; detecting, at the processor, a pose of an entity from the received plurality of optical images, identifying region of interests (ROIs) from the detected pose and calculating thermal co-ordinates from the identified ROIs; based on the calculated thermal co-ordinates and the captured plurality of thermal images, determining, at the processor, temperature at the identified ROIs; and comparing, at the processor, the obtained temperature at the identified ROIs with a predetermined threshold value and generating, an alert when the compared temperature at the ROIs is greater than the predetermined threshold value.
[0011] In an embodiment, the generated alert may be displayed either over a display device or may be generated as an audio alert.
[0012] In an embodiment, the processor comprises a learning engine to process the plurality of optical images and the plurality of thermal images.
[0013] In an embodiment, the learning engine may be any of a neural network, a machine learning model, and an artificial intelligence model.
[0014] In an embodiment, the optical image capturing device and thermal image capturing device may be operatively coupled to the computing device.
[0015] In an embodiment, the thermal image capturing device may be any of a thermal sensor and an infrared temperature sensor.
[0016] In an embodiment, the thermal image capturing device may captures images of the plurality of entities present within a field of view (FOV) of the image capturing device.
[0017] An aspect of the present disclosure provides a system for determining body temperature of a plurality of entities at an instance, said system comprising: a processing engine of a computing device comprising a processor coupled with a memory, the memory storing instructions executable by the processor to: receive a plurality of optical images and a plurality of thermal images corresponding to each of an entity of the plurality of entities, the plurality of optical images being captured using an optical image capturing device and the plurality of thermal images being captured using a thermal image capturing device; detect a pose of an entity from the received plurality of optical images, identifying region of interests (ROIs) from the detected pose and calculating thermal co-ordinates from the identified ROIs; based on the calculated thermal co-ordinates and the captured plurality of thermal images, determine temperature at the identified ROIs; and compare at the processor, the obtained temperature at the identified ROIs with a predetermined threshold value and generating, an alert when the compared temperature at the ROIs is greater than the predetermined threshold value.

BRIEF DESCRIPTION OF DRAWINGS
[0018] The accompanying drawings are included to provide further understanding of the present disclosure and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure. The diagrams are for illustration only, which thus is not a limitation of the present disclosure.
[0019] FIG. 1 illustrates an exemplary block diagram for a system to detect temperature of one or more entities, in accordance with an embodiment of the present disclosure.
[0020] FIG. 2 illustrates exemplary functional components of the proposed system in accordance with an embodiment of the present disclosure.
[0021] FIG. 3 illustrates an exemplary flow diagram for a method to detect temperature of one or more entities, in accordance with an embodiment of the present disclosure.
[0022] FIG. 4A illustrates an exemplary representation of a learning engine in accordance with an embodiment of the present disclosure
[0023] FIG. 4B illustrates a flow diagram for a proposed method to detect temperature of one or more entities, in accordance with an embodiment of the present disclosure.
[0024] FIG. 5 illustrates an exemplary computer system in which or with which embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure.

DETAILED DESCRIPTION
[0025] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims.
[0026] The present disclosure relates, in general, to public health. In particular, the present disclosure relates to a means to monitor temperature of a group of people.
[0027] FIG. 1 illustrates an exemplary block diagram for a system 100 to detect temperature of one or more entities, in accordance with an embodiment of the present disclosure.
[0028] In an aspect, the system 100 can be implemented to scan and check temperature of the one or more entities, without requiring them to stop to have their temperature measured.
[0029] In another aspect, the system 100 can be implemented at any location such as indoor or outdoor, without significant change in configurations, i.e., the system 100 may be versatile.
[0030] In another aspect, the system 100 may be capable of scanning different regions of interest (ROI) on the one or more entities for temperature detection, such as forehead, hand, face, ,and nostrils and the like. Further, it is not required for the one or more entities to be aligned for temperature measurement.
[0031] In an aspect, the system 100 can receive input from an optical image capture device 102 that is capable of capturing images in RGB (Red, Green and Blue), such as an RGB camera, which is a Charged Coupled Device (CCD) device configured to capture real time video feed with high resolution (high fps). The optical image capture device 102 can have a USB interface with the system 100. In an exemplary embodiment, the frames are captured using a set of instructions for frame capture using Python, Open CV, C, C++ or a combination thereof.
[0032] In another embodiment, the system 100 can receive input from a thermal image capture device 104 such as a thermal camera, which can be a radiometric sensor array with a specific field of view (FOV), to capture heat radiation in the FOV. The thermal image capture device 104 can have a USB interface with the system 100.
[0033] In another embodiment, the system 100 can include a processing engine 106, which can include processor(s) 108 and a memory 110, the memory 110 storing instructions executable by the processor(s) to detect temperature of one or more entities.
[0034] In another embodiment, the thermal image capture device 104 and the optical image capture device 102 may be set up such that they have the same FOV, and they can be calibrated such that RGB images received from the optical image capture device 102 is mapped to the thermal images captured by the thermal image capture device 104.
[0035] In another embodiment, the processing engine 106 receives data from the optical image capture device 102. The data can include images in FOV of the optical image capture device 102, which can include the one or more entities. Using an image processing methodology, the processing engine 106 detects (152) pose and/or face of the one or more entities and one or more ROIs on the one or more entities. Once the pose and ROI are detected, the processing engine 106 can calculate (154) thermal coordinates for the ROIs.
[0036] In an embodiment, the optical image capture device 102 may include all digital cameras and digital video cameras. These camera devices include cell phones, PDAs, telephones, video camcorders, digital video cameras, digital SLRs, laptops, netbooks, tablet computers and video teleconferencing systems.
[0037] In an embodiment, the thermal imaging capture device 104 may include a thermal camera. The objective of the camera is to measure temperature without a need for any contact. The thermal cameras can be usually used in an industrial sector to detect temperature variations and to be able to control and modify it. The thermal cameras can be mostly used in the healthcare sector and are used to measure human temperature without having to touch the patient. These cameras are capable of analyzing, with a high degree of precision, the body temperature of people, facilitating an immediate detection of feverish pictures.
[0038] Typically, the thermal imaging capture device 104 may be used to measure an entity’s body temperatures work and works by capturing a thermal emission of the entities in an infrared spectrum range to detect heat sources and measure their temperature. Then these devices make use of advanced algorithms to measure the temperature with a high degree of precision, reaching an accuracy of +/- 0.3ºC with use of a calibrating device called “black body” that is maintained at a constant temperature for what has a fixed and known thermal emissivity. The device 104 can incorporate artificial intelligence for pose estimation, which can allow each entity to be identified to measure their temperature.
[0039] In an exemplary embodiment, the processing engine 106 can employ a learning engine 112 such as neural networks, machine learning and other artificial intelligence (AI) – based learning to process the received data from the optical image capture device 102 and the thermal image capture device 104. In a way of example and not as a limitation, the learning engine 112 may be a Neural network used, named ResNet 18 (Ref. FIG. 4A).
[0040] In another embodiment, the processing engine 106 can receive data from the thermal image capture device 104. The data can include thermal images in FOV of the thermal image capture device 104, which can include the one or more entities. From the received data and based on thermal coordinates calculated for the ROIs of the one or more entities, temperature of the one or more ROIs of the one or more entities is obtained (156).
[0041] If the obtained temperature of any of the one or more entities is greater than a predetermined threshold value, an alert is generated (158). The threshold value can be obtained based on information provided by medical health resources.
[0042] In another embodiment, the system 100 can include a display device 114, which can display information pertaining to any or a combination of data received from the optical image capture device 102, pose and ROI detected (152) for the one or more entities in FOV of the optical image capture device 102, calculated thermal coordinates (154) for the one or more entities, data received from the optical image capture device 102, the obtained temperature (156) of the ROIs and any alert generated (158).
[0043] In another embodiment, the alert generated (158) can be through a visual aid such as flashing LED lamps, displaying of a message etc. or through an audio aid such as an alarm.
[0044] In another embodiment, the system 100 can include a memory device 116 which can store the above-mentioned information.
[0045] FIG. 2 illustrates exemplary functional components of the proposed system 100 in accordance with an embodiment of the present disclosure.
[0046] In an aspect, the system 100 may comprise one or more processor(s) 202. The one or more processor(s) 202 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) 202 are configured to fetch and execute computer-readable instructions stored in a memory 206 of the system 100. The memory 206 may store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory 206 may comprise any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0047] The system 100 may also comprise an interface(s) 204. The interface(s) 204 may comprise a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 204 may facilitate communication of system 100. The interface(s) 204 may also provide a communication pathway for one or more components of the system 100. Examples of such components include, but are not limited to, processing engine(s) 208 and data 210.
[0048] The processing engine(s) 208 may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) 208. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) 208 may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) 208 may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) 208. In such examples, the system 100 may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to system 100 and the processing resource. In other examples, the processing engine(s) 208 may be implemented by electronic circuitry.
[0049] The data 210 may comprise data that is either stored or generated as a result of functionalities implemented by any of the components of the processing engine(s) 208 or the system 100.
[0050] In an exemplary embodiment, the processing engine(s) 208 may include an optical image and thermal image receiving engine 212, a pose detecting engine 214, a temperature identifying engine 216, a comparison engine 218, and other engine (s) 220.
[0051] In an embodiment, optical image and thermal image receiving engine 212, receives a plurality of optical images and a plurality of thermal images corresponding to each of an entity of the plurality of entities. The plurality of optical images are captured using an optical image capturing device and the plurality of thermal images are captured using a thermal image capturing device. The optical image capturing device and thermal image capturing device may be operatively coupled to the computing device. In an aspect, the thermal image capturing device may be any of a thermal sensor and an infrared temperature sensor. In an aspect, the thermal image capturing device may capture images of the plurality of entities present within a field of view (FOV) of the image capturing device.
[0052] In an embodiment, a pose detecting engine 214, detects a pose of an entity from the received plurality of optical images. Region of interests (ROIs) are identified from the detected pose and thermal co-ordinates from the identified ROIs are calculated.
[0053] In an embodiment, a temperature identifying engine 216, determines temperature at the identified ROIs based on the calculated thermal co-ordinates and the captured plurality of thermal images.
[0054] In an embodiment, a comparison engine 218, compares the obtained temperature at the identified ROIs with a predetermined threshold value and generates an alert when the compared temperature at the ROIs is greater than the predetermined threshold value. In an aspect, the generated alert may be displayed either over a display device or is generated as an audio alert. In an aspect, a processor comprises a learning engine to process the plurality of optical images and the plurality of thermal images. The learning engine may be any of a neural network, a machine learning model, and an artificial intelligence model.
[0055] FIG. 3 illustrates an exemplary flow diagram for a method to detect temperature of one or more entities, in accordance with an embodiment of the present disclosure. In an embodiment, the method 300 can be implemented on a computing device.
[0056] In another embodiment, the method 300 can include at 302 the step of receiving data from the optical image capture device and at 304, the step of detecting pose and/or face of one or more entities in the FOV of the optical image capture device. The method (300) may further include at 306, the step of identifying ROIs on the one or more entities and at 308, the step of calculating thermal coordinates for the ROIs of the one or more entities.
[0057] Furthermore, the method (300) may include at 310, the step of receiving data from the thermal image capture device, at 312, the step of obtaining temperature detected at the ROIs of the one or more entities and at 314, the step of generating an alert if detected temperature is higher that a predefined threshold.
[0058] Finally, the method (300) may include at 316, the step of displaying the alert at a display device; and at 318, the step of storing log data.
[0059] FIG. 4A illustrates an exemplary representation (400) of a learning engine in accordance with an embodiment of the present disclosure. In an exemplary embodiment, the learning engine may be a neural network ResNet 18 but not limited to it and may include the following steps:
• USB Device (RGB and thermal Camera) are connected to the device
• Python Script starts capturing the data from RGB and THERMAL Cameras
• RGB images are passed to a neural network, which gives output in list of list format where each list consists of coordinates of various points such as eyes, nose, ear etc.
• After the coordinates are received, the forehead region is calculated using the proposed method.
• After the desired ROI is received, the temperature in that area is determined using thermal camera array data.
• Tools used: Python, OpenCV, Tensorflow, Tensorrt but not limited to the like.
[0060] FIG. 4B illustrates a flow diagram 450 for a proposed method to detect temperature of one or more entities at an instance, in accordance with an embodiment of the present disclosure.
[0061] The method may include at block 452, a step for receiving a plurality of optical images and a plurality of thermal images corresponding to each of an entity of the plurality of entities. The plurality of optical images may be captured using an optical image capturing device and the plurality of thermal images being captured using a thermal image capturing device. At block 454, the method may include the step for detecting a pose of an entity from the received plurality of optical images, and region of interests (ROIs) from the detected pose may be identified to calculate thermal co-ordinates from the identified ROIs. At block 456, based on the calculated thermal co-ordinates and the captured plurality of thermal images, the method may include the step for determining temperature at the identified ROIs. Further, at block 458, the method (400) may include the step for comparing obtained temperature at the identified ROIs with a predetermined threshold value and an alert is generated when the compared temperature at the ROIs is greater than the predetermined threshold value.
[0062] FIG. 5 illustrates an exemplary computer system in which or with which embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure.
[0063] As shown in FIG. 5, computer system 500 includes an external storage device 510, a bus 520, a main memory 530, a read only memory 540, a mass storage device 550, communication port 560, and a processor 570. A person skilled in the art will appreciate that computer system may include more than one processor and communication ports. Examples of processor 570 include, but are not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), Motorola® lines of processors, FortiSOC™ system on a chip processors or other future processors. Processor 570 may include various modules associated with embodiments of the present invention. Communication port 560 can be any of an RS-232 port for use with a modem-based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fibre, a serial port, a parallel port, or other existing or future ports. Communication port 560 may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system connects.
[0064] Memory 530 can be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read only memory 540 can be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for processor 570. Mass storage 550 may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), e.g. those available from Seagate (e.g., the Seagate Barracuda 7200 family) or Hitachi (e.g., the Hitachi Deskstar 7K1000), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g. an array of disks (e.g., SATA arrays), available from various vendors including Dot Hill Systems Corp., LaCie, Nexsan Technologies, Inc. and Enhance Technology, Inc.
[0065] Bus 520 communicatively couples processor(s) 570 with the other memory, storage, and communication blocks. Bus 520 can be, e.g. a Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects processor 570 to software system.
[0066] Optionally, operator and administrative interfaces, e.g. a display, keyboard, and a cursor control device, may also be coupled to bus 520 to support direct operator interaction with computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port 560. External storage device 510 can be any kind of external hard-drives, floppy drives, IOMEGA® Zip Drives, Compact Disc - Read Only Memory (CD-ROM), Compact Disc - Re-Writable (CD-RW), Digital Video Disk - Read Only Memory (DVD-ROM). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[0067] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE PRESENT DISCLOSURE
[0068] The present disclosure provides systems and methods to measure body temperature of multiple entities at an instance.
[0069] The present disclosure provides systems and methods to capture digital and thermal images of the entities and determine body temperature of the entities.
[0070] The present disclosure provides systems and methods to provide a contact less mechanism for measuring body temperature of multiple entities.

,CLAIMS:1. A method for determining body temperature of a plurality of entities at an instance, said method comprising:
receiving, at a processor of a computing device, a plurality of optical images and a plurality of thermal images corresponding to each of an entity of the plurality of entities, the plurality of optical images being captured using an optical image capturing device and the plurality of thermal images being captured using a thermal image capturing device;
detecting, at the processor, a pose of an entity from the received plurality of optical images, identifying region of interests (ROIs) from the detected pose and calculating thermal co-ordinates from the identified ROIs;
based on the calculated thermal co-ordinates and the captured plurality of thermal images, determining, at the processor, temperature at the identified ROIs; and
comparing, at the processor, the obtained temperature at the identified ROIs with a predetermined threshold value and generating, an alert when the compared temperature at the ROIs is greater than the predetermined threshold value.
2. The method as claimed in claim 1, wherein the generated alert is displayed either over a display device or is generated as an audio alert.
3. The method as claimed in claim 1, wherein the processor comprises a learning engine to process the plurality of optical images and the plurality of thermal images.
4. The method as claimed in claim 3, wherein the learning engine is any of a neural network, a machine learning model, and an artificial intelligence model.
5. The method as claimed in claim 1, wherein the optical image capturing device and thermal image capturing device are operatively coupled to the computing device.
6. The method as claimed in claim 1, wherein the thermal image capturing device is any of a thermal sensor and an infrared temperature sensor.
7. The method as claimed in claim 1, wherein the thermal image capturing device captures images of the plurality of entities present within a filed of view (FOV) of the image capturing device.
8. A system for determining body temperature of a plurality of entities at an instance, said system comprising:
a processing engine of a computing device comprising a processor coupled with a memory, the memory storing instructions executable by the processor to:
receive a plurality of optical images and a plurality of thermal images corresponding to each of an entity of the plurality of entities, the plurality of optical images being captured using an optical image capturing device and the plurality of thermal images being captured using a thermal image capturing device;
detect a pose of an entity from the received plurality of optical images, identifying region of interests (ROIs) from the detected pose and calculating thermal co-ordinates from the identified ROIs;
based on the calculated thermal co-ordinates and the captured plurality of thermal images, determine temperature at the identified ROIs; and
compare at the processor, the obtained temperature at the identified ROIs with a predetermined threshold value and generating, an alert when the compared temperature at the ROIs is greater than the predetermined threshold value.
9. The system as claimed in claim 8, wherein the generated alert is displayed either over a display device or is generated as an audio alert.

10. The system as claimed in claim 8, wherein the thermal image capturing device is any of a thermal sensor and an infrared temperature sensor.