Description
OBJECTIVE
The main objective of this project is to identify the Anti-Poaching of Trees & Wild animals etc… by using IoT and Deep Learning.
IOT based anti-poaching system using Raspberry Pi
ABSTRACT
Poaching in today’s world is one of the most significant threats to wildlife. Poachers use different methods to capture animals. Many commercial poachers use military-grade weapons along with arrows and spears to hunt wildlife. Sometimes, objects called snares (a set of wires tied to trees configured to capture any animal by their leg or neck that gets into it) are also implemented. Poachers also trap the animal into large nets, known as trap nets, pitfall traps (a vast pit dug into the ground that is layered with leaves and plants), or baits. In this paper, we suggest a new solution that operates in real-time to pursue the cause of wildlife conservation by preventing the poaching of any species of animals – endangered or non-endangered by profit-hungry poachers with the help of Deep Learning and the Internet of Things (IoT). In comparison to previous methods in the same domain, it presents an alternate approach, in the form of a monitoring system that can track poaching activity and predict poachers’ behavior, and alert forest authorities for any suspicious crime.
INTRODUCTION
The global tiger population has dropped over 95% from the start of the 1900s and has resulted in three out of nine species being brought on the brink of extinction. At this rate, these creatures will be endangered and will eventually face extinction. These activities are continuously increasing in the world due to the decrease in the population of the animals and the increase in the number of the rarity of some species of animals. In order to protect wildlife and their habitats from poaching and illegal trade various wildlife conservation agencies are established across the globe. Many rangers are stationed to patrol throughout the conservation areas. Many local communities, wildlife populations, and the environment is negatively affected by wildlife poaching. The animal parts are sold as novelty items and are sold for their “medicinal” properties in various black markets. For example, Ivory is used by the Chinese for arts and utility purposes, the Americans to make gun and knife handles as well as decorative details on these weapons.
EXISTING SYSTEM
- There was Already IoT based Anti-poaching system alarm system
- There will be some delay in an alert system with the Alarm
DISADVANTAGES
- In this project we just need to connect the internet to that device then only it will update the data to the Receiver (or) cloud.
PROPOSED SYSTEM
This research suggests the use of computer vision to make an intelligent monitoring system that will send a report back to the rangers when any criminal activity takes place within the forest region. Various efforts had been undertaken by the scientific community to develop systems that will only report back to the rangers after the incidence of poaching had happened or when it absolutely was occurring. In one of those efforts, a new solution was proposed by utilizing both very limited data about the forest and human knowledge to predict and analyze poaching patterns. It proposed an approach to assemble quantitative information through a questionnaire built upon a clustering-based division of the conservation area from domain experts. Additionally, it also proposed algorithms that exploit qualitative and quantitative information provided by the domain experts to reinforce the dataset and improve learning.
ADVANTAGES
- Intelligent monitoring will be done using Deep learning.
- If any activity takes place within this region it sends the data immediately to the forest officer.
BLOCK DIAGRAM
BLOCK DIAGRAM EXPLANATION
- In this system, the different data are analyzed such as temperature, Tilt and camera detect the motion in that region.
- The Temperature sensor detects the temperature in the atmosphere
- The camera is the device that detects the motion happening in that region.
CONCLUSION
Considering the fact that wildlife habitats and species around the world are facing a crisis if we take the conventional reason why wildlife animals are being affected, poaching comes out to be one of the vital reasons which lead to an unbalanced chain contributing to the extinction of species. For this issue to be solved. In this paper, we provided the survey-based idea for classifying variations of Sound generated by animals and humans, especially foot sound. This detection will further help in identifying poaching scenarios in wildlife habitats which when prevented can help in providing contribute to our wildlife conservation. So, it has been necessary to stop poaching so that we can balance the ecosystem
HARDWARE REQUIREMENTS
- Raspberry Pi
- Camera
- Temperature sensor
- Tilt sensor
SOFTWARE REQUIREMENTS
- Program: Python
- Platform: Python 3 IDLE
- Raspberry pi os: Raspian os
- Library: opencv
- Deep learning
REFERENCES
- Bishop, C. M. (2006) Pattern Recognition and Machine Learning
Schmidhuber, J. (2015). Deep Learning in Neural Networks: An Overview. Neural Networks 61: 85-117.
Bengio, Y., LeCun, Y., Hinton, G. (2015). Deep Learning. Nature 521: 436-44.
Goodfellow, I., Bengio, Y. and Courville, A. (2016) Deep Learning. MIT Press. - An extensive list of references can also be found at https://github.com/terryum/awesome-deep-learning-papers and http://deeplearning.net/reading-list/
- Report https://timesofindia.indiatimes.com/india/india-lost- 110-tigers-491-leopards-in-19-poaching-up- reort/articleshow/73052610.cms
- Cause of poaching: http://www.animalmatters.org/facts/wildlife/4
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