Description:The present invention is a system and method for automated forest monitoring using drones and computer algorithms. The system includes a drone equipped with a camera that captures images of the forest, which are then transmitted to a server , for analysis with the help of a micro- processing unit. The server is equipped with four built-in machine learning models to analyze the images and provide accurate detections of animals, forest fires, poaching-related activities, and deforestation.
Upon receiving the images, the machine learning models work simultaneously to identify the animals present in the image, count their numbers, and classify them into two categories, namely Endangered Animals and Abundant Animals. The classification is based on the conservation status of the animals, and the system generates real-time alerts if any endangered animals are detected, enabling authorities to take necessary actions promptly.
The machine learning models also analyze the images for the presence of forest fires, poaching-related activities, and deforestation. If any such activities are detected, the system generates real-time alerts, enabling authorities to take appropriate actions to prevent further damage.
The system's unique feature is its ability to automate forest monitoring using drones and machine learning algorithms, making it easier and cost-effective to detect and prevent forest-related crimes. The system provides an efficient way to monitor and protect the forest's biodiversity, allowing authorities to take proactive steps to prevent environmental damage.
The system's benefits include improved accuracy, reduced costs, and increased efficiency in monitoring forest activities. The system's automation reduces the need for manual intervention, making it more reliable and consistent. The system's potential applications include monitoring wildlife populations, detecting forest fires, and preventing deforestation.
In conclusion, the present invention provides a novel system and method for automated forest monitoring using drones and machine learning algorithms, which addresses the shortcomings of traditional forest monitoring methods. The invention's benefits include improved accuracy, reduced costs, and increased efficiency, making it an ideal solution for forest monitoring and protection. , Claims:We Claim:
1. An automated system for forest monitoring comprising drone, camera, a micro-processing unit and server wherein the system is capable of capturing photographs of vast forest areas, which is analyzed to identify changes in the environment, including tree loss or growth wherein the machine learning algorithms find, count, and categorize species based on their level of conservation, thereby gathering information for conservation efforts and safeguarding endangered species and the system can also detect forest fires in real-time using drone-acquired images, potentially reducing damage and shortening response times.
2. An automated system for forest monitoring as claimed in claim 1, wherein the camera attached in the drone captures the image and sends the data to the server through the micro-processing unit.
3. An automated system for forest monitoring as claimed in claim 1 wherein the machine learning algorithms identify and notify authorities of the occurrence of forest fires in real-time using drone-acquired images which as a result reduces the damage by shortening the response time.
4. An automated system for forest monitoring as claimed in claim 1 wherein the machine learning algorithms identify and notify authorities of poaching-related behaviors in real-time which has a quicker response time and a greater likelihood of apprehending poachers such as the location of hunting traps or the movement of hunters.
5. An automated system for forest monitoring as claimed in claim 1 has additional features that identify and notify authorities of deforestation activities in real-time wherein the technology can detect illicit tree cutting activities by examining the images taken by the drone,that allows for a quicker response and increases the likelihood that the offenders will be apprehended.
6. An automated system for forest monitoring as claimed in claim 1 wherein the technique entails utilizing a drone to take pictures of the forest, then using machine learning algorithms to identify, count, and categorize any animals in the pictures.  

7. An automated system for forest monitoring as claimed in claim 1 wherein the present invention provides an efficient and effective means of forest management, conservation and protection.