Project Description/project implementation overview:
Bot for Surveillance of Forest and Large Farms project aims to develop an IoT enabled bot which can be used for surveillance and monitoring of forests and large farms. The bot will be equipped with a camera and motion sensors enabling it to detect animals and humans in its vicinity. The bot will also be equipped with GPS and wireless communication technologies to enable it to send real time data to a remote location.
The bot will be equipped with an object recognition technology powered by computer vision. This will enable it to detect and differentiate between animals and humans. It will also be able to recognize and distinguish between different types of animals, enabling it to provide accurate information regarding the presence of certain species within the monitored area.
The bot will also be equipped with a data logging system, enabling it to store information about the number of animals and humans present in the area. This information can be used to understand the population trends of various species and to monitor any changes.
The data collected by the bot can be used to alert local law enforcement or forestry services of any suspicious activity. The information can also be used to identify areas which need extra protection or conservation efforts.
Finally, the data collected can be used to identify any potential threats to the environment and to plan conservation efforts more effectively.
Hardware and software requirements for project implementation:
Hardware Requirements:
- Camera: The most important component of this system is the camera. It must have high resolution and wide field of view so that it can capture images of the entire forest or farm. It must also be waterproof and weatherproof so that it can operate in outdoor conditions.
- Sensors: The system must have various sensors such as temperature, humidity, pressure, wind speed and direction. These sensors will help monitor the environment in the forest or farm.
- Raspberry Pi/NODE MCU: A microprocessor such as raspberry pi is required to receive data from the sensors and process them
- DHT11 sensor: It is used to check the temperature and humidity of the soya bean field.
- Computing Unit: This system requires a powerful computing unit to process the image data and sensor data. It should be able to run advanced algorithms for object detection, facial recognition, and other computer vision tasks.
- Communication Unit: The system must also have a communication unit to send and receive data from the devices and sensors.(GSM/GPRS/GPS)
- Power Supply: The system must have a reliable power supply to support all the hardware components. It could be powered by solar panels or batteries.
- Network: The system must have a secure network connection so that it can be remotely monitored and controlled. This could be a wireless network or a wired network.
- Thingspeak: To check the current status of the sensors data uploaded to cloud, thingspeak dashboard is used to monitor it.
Software Requirements
- Computer Vision Software: This software will be used for object detection, tracking, and recognition. It should be capable of detecting objects such as animals, crops, and humans in real-time. It should also be able to recognize the presence of suspicious activity and alert the user. Examples of such software include OpenCV, TensorFlow, and Darknet.
- Programming Language: A programming language such as Python is needed to program the Raspberry pi.
- IoT Enabled Software: This software will be used to connect the various sensors, cameras, and devices to the bot. It should be able to communicate with the bot and send data in real-time. It should also be able to receive commands from the bot and execute them accordingly. Examples of such software include Node-RED, Node.js, python and Arduino.
- AI and Machine Learning Software: This software will be used to analyze the data collected by the bot and make decisions. It should be able to recognize patterns and detect anomalies in the data. Examples of such software include Google Cloud Platform, AWS, and Microsoft Azure.
- Cloud Computing Software: This software will be used to store and process the data collected by the bot. It should be able to securely store the data and provide access to it when needed. Examples of such software include AWS, Google Cloud.
What You Will Learn? By working on the project
- Understanding Computer Vision and its applications.
- Learning about different types of sensors and their usage.
- Learning about different types of IoT and its applications.
- Getting hands-on experience with developing and programming a IoT-enabled bot for surveillance and monitoring of forest and large farms.
- Understanding the importance of data analysis for creating accurate models and algorithms.
- Developing skills for developing and deploying AI-enabled bots for surveillance and monitoring.
- Understanding the importance of creating secure and reliable communication networks for carrying out surveillance and monitoring tasks.
- Understanding the importance of data security and privacy for creating secure systems.
Curriculum
- 9 Sections
- 25 Lessons
- 15 Hours
- Module 1: Introduction to IoT and Embedded Systems2
- Module 2: Setting up the Hardware2
- Module 3: Programming the Microprocessor2
- Module 4: Cloud Computing and gateway Management Application3
- Module 5: gateway integration2
- Module 6: Algorithm Development2
- Module 7: Project Implementation and Testing3
- Module 8: Conclusion and Next Steps3
- Module 9: Building a Portfolio for IoT Jobs6
- 9.1Overview of the importance of having a portfolio in the IoT field
- 9.2How to document the work done during the project, including code, documentation, and test results
- 9.3How to present the portfolio in an effective way to showcase the skills and knowledge gained during the project
- 9.4How to tailor the portfolio for different types of IoT job opportunities (e.g. embedded systems engineer, IoT developer, IoT consultant
- 9.5Tips for networking and reaching out to companies in the IoT field
- 9.6How to continue learning and staying updated on the latest developments in the IoT field
