Complex-Animal-Movement-Capture-and-Live-Transmission-CAMCALT-

The main python file is "errorda.py" which branches into and calls other python files and the whole program files are packaged into a clickable shell file named "Camcal1t.sh"

Please feel free to contact me through linkedin if you have any doubts regarding the project: https://linkedin.com/in/shreyas-ramachandran-srinivasan-565638117/

To see photos and videos from presentation/demo, visit: https://ssr1996.wixsite.com/shreyas-ssr/projects-patents

User manual for said CAMCALT device: https://www.slideshare.net/slideshow/embed_code/key/t1MtqZh74rUYSy

INTRODUCTION

Our project Complex Animal Movement Capture And Live Transmission (CAMCALT) is a device specifically tailored to the need of a forest surveillance and monitoring system. The objective of the project is to eradicate the existing disadvantages of the Forest Trap Camera’s and integrate the latest technologically developed “Internet of Things” (IoT) into the device for Live feed wirelessly from any part of the world. The user-friendly UI is via an application that runs on a Raspberry Pi 3 Model B microcomputer. It is used to monitor the forests, animal movements and Poacher Detection. By this, 24 hours surveillance has been made possible that hunting and poaching can be prevented. Prevention of poaching of any animal by illegal poachers cabe done in forest areas. Forests can be more secure like a military restricted area. CAMCALT is an intelligent over watch for the forest landscape. In large numbers, you can have the whole forest under your control.

LITERATURE REVIEW

In the existing trap camera system, the forest ranger usually manually retrieves memory cards in the trap cameras each 30 days and replaces them with new memory cards. Then, the photographs stored in old memory card are reviewed. By then, if any crime, poaching has occurred, forest officers are not in a position to do anything about this situation. But in our proposed concept, we are integrating the latest technologically developed “Internet of Things” (IoT) into the device for Live video feed which is done wirelessly from any part of the world. This makes our proposed system much better than the disadvantageous trap camera system. the cost down for the home automation system. The global trap cameras market is valued at 64 million US$ in 2017 and will reach 77 million US$ by the end of 2025, growing at a CAGR of 2.7% during 2018-2025. Years considered for this report Base year: 2017 Estimated year: 2018 Forecast period: 2018–2025.

COMPONENTS EXPLANATION

CAMCALT is abbreviated as Complex Animal Movement Capture and Live Transmission. As the abbreviated tag elucidates us clearly that it helps in capturing the complex animal movement under intense period of time providing a live feed of the situation. The prototype consists of the following components to carry out the operation:

A. Central Microcontroller – Raspberry Pi 3 Model B The prototype is designed with a Central Microcontroller – Raspberry Pi 3 Model B which has a Broadcom BCM2837 64bit ARMv7 Quad Core Processor powered Single Board Computer running at 1.2GHz, 1 GB RAM, BCM43143 Wi-Fi on board, Bluetooth Low Energy (BLE) on board, 40pin extended GPIO, 4 x USB 2 ports, 4 pole Stereo output and Composite video port, Full size HDMI, CSI camera port for connecting the Raspberry Pi camera, DSI display port for connecting the Raspberry Pi touch screen display, Micro SD port for loading your operating system and storing data. The controller is interfaced with a Passive Infra-red sensor, Global Positioning Sensor, Raspberry Pi Camera.

B. Pi Camera Module PI camera module captures 2592 * 1944 pixel static images and also supports 1080p at 30fps @ 60fps and 540 * 480p 60/90 video recording. Camera module is interfaced with the central microcontroller Raspberry Pi 3.

C. GPS Module This module named Neo 6M-0-00-1 U-Blox operating at 5V DC. Global Positioning System is used for tracking the location of each Device placed in various parts. The Global Positioning System is connected up with satellites, ground stations, and receivers. Once the receiver calculates its distance from four or more satellites, it knows exactly where you are. GPS locks the exact position of that particular Device if Motion Detected.

D. Motion Sensor The A passive infrared sensor (PIR sensor) [1] is an electronic sensor that measures infrared (IR) radiation being emitted from objects in its field of view. They are most often used in PIR-based motion detectors. When the sensor is idle, both slots detect the same amount of IR, the ambient amount radiated from the room or walls or outdoors. When a warm body like a human or animal passes by, it first intercepts one half of the PIR sensor, which causes a positive differential change between the two halves. Thus automatically the PIR sensor is trigger when any animal is caught within its radius.

E. USB Power In Rechargepower bank of any capacity, here, 2800 mAH is used (operating voltage of 5V DC), can be used to provide supply to central microcontroller. The microcontroller used will separate and supply the required amount of power to each hardware component. This battery power pack is rechargeable and can get charged and used again and again.

IV. CONNECTING TO THE INTERNET The forest officials or the rangers at the control center can continuously control and monitor the device in real time. The device helps them to have a complete control of the forest bed remotely. From their computer they can achieve a graphical desktop based sharing system which uses Remote frame buffer protocol (RFBP) through which the interace is transmitted in real time from the device to the control centre.

GRAPHICAL USER INTERFACE

The application on the Raspberry Pi microcomputer is developed using python language and made into an executable shell file. When the file is double clicked, it automatically opens the execution terminal.

 CASE 1: If any warm blooded animal or human interferes the zone of IR rays it automatically displays “Motion detected” and turns on the Camera and GPS and sends a default notification is sent as a message to the in charge security’s personal phone [2].  CASE 2: If no warm blooded animal or human interferes the zone of IR rays it displays no Animal is detected and set the camera and GPS to rest mode. CAMCALT is designed in such a way that every processing and monitoring is user friendly and can be operated by everyone easily. As mentioned earlier once a Pop up frame appears, a wide ray of options can be selected according to the in-charge person’s requirement. The GUI frame is user friendly and the following processes can be done:  Quit – Quits the program.  Take Picture – We can immediately take a series of photos in a burst, this is automatically saved to a default location.  Live Feed – We can get live feed of what the current situation is from our device camera.  Record Video – The live feed can be recorded and the video files can be automatically saved to a default location.  Poacher Detection – Pre-trained Poachers can be easily recognized by our Image Processing Algorithms.  Train Poacher to Camcalt – Repeated Poachers can be trained to the device to be recognized in the future by our Image Processing Algorithms  GPS Location – The location of the device can also be found.

A. Take picture, record video and live video feed As the user-friendly UI pops up like that of Fig 5 when motion is detected, the user–in-charge has the following options here:  “Take Photo”: This option gives the user - in - charge an option to take a high quality photograph/image (5 Mega - Pixels) of what is in the field of view of the camera when the motion is detected.  “Record Video”: This option gives the user-in - charge an option to record a high quality 10 second video (1080p 24 fps) of whatever is in the field of view of the camera when pressed.  “Live Feed”: This option gives the user - in - charge a high quality video feed (1080p 24 fps) of whatever is in the field of view of the camera when the motion is detected.

B. Getting GPS Location As the user-friendly UI pops up like that of Fig 5 when motion is detected and the “GPS Location” button from this UI gives the user-in -charge an option to get the current GPS location coordinates of the CAMCALT device when pressed, this will be useful when we use an array of CAMCALT devices in the forest so as to identify from which device/ location of the forest the motion got detected.

C. Train Poacher to CAMCALT and poacher detection The most special and powerful feature of CAMCALT is Poacher Detection. This Feature uses the Image Processing techniques to detect the Poacher using the 4 cores of the powerful BCM2837 Processor powered by 1 GB RAM. By using HSV to split-analyze the images and Haar Cascade Detection to match the existing samples with the testing image. The process of Poacher Detection is to first Train the Poacher to the Device then followed by Poacher Detection. Figure 6. Train Poacher to CAMCALT Here, as the user-friendly UI pops up like that of Fig 5 when motion is detected and the “Train Poacher to CAMCALT” button is pressed [3], one will get an option to key in the name or identity of that Poacher. Then, show the face of the poacher to the camera with good brightness. If there is a face, the application will detect the face with a green box. By default, the application is set to capture 20 samples. But it can be modified to one’s wish. As soon as the application captures the necessary images, the camera preview window closes automatically. Now, the device is trained to that particular poacher, and whenever or wherever (i.e. from any device placed) that poacher is read in any device’s camera, he will be automatically detected. That is because that poacher’s facial features will be regularly compared and matched with the live person’s face to check for a match. If it matches, he will be immediately detected. Everything happens in real-time. There is never a time delay between detections. The program executes in micro-seconds, so the time lapse is negligible. Here, as the user-friendly UI pops up like that of Fig 5 when motion is detected and the “Poacher Detection” button is pressed, the “Face Recognition Window” pops up. Now whenever a face is shown in front of the camera, it immediately tries to find a match. If there is, then it shows with a green box around the face with a name and identity of the poacher. Else, it displays “Unknown” (See Fig 6) .