A Smart Wireless System to Automate Production of Crops and Stop Intrusion Using Deep Learning

A Smart Wireless System to Automate Production of Crops and Stop Intrusion Using Deep Learning

₹9,000.00
Product Code: Embedded - Artificial Intelligence
Availability: In Stock
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Product Description

Aim:

        Aim of the project is to reduce animal-vehicle collision on roadsides using machine learning and raspberry pi.

 

Abstract:

        Animal-Vehicle collisions are a significant public health concern in various countries. The annual economic cost exceeds over a billion from injuries property damage. From 2011-2012 till July 2019, as many as 11,915 stray animals including dog, cats, cattle and goat were injured in road accidents in different part of the city, data prepared by Nagpur Municipal corporation veterinary department has revealed. According to State of India's Environment 2019 e-book, 161 wild animals died in road, rail accidents in 2018.According to the accident research study conducted by JPResearch India Pvt. Ltd. for the Ahmedabad-Gandhinagarregion (cities of India), for the duration February 2014 to January 2015, total 206 road traffic accidents were recorded and these were influenced by three main factors i.e. human, vehicle, infrastructure or a combination of them. From the record 6% (12 accidents) were due to animals on the road.

 

        Various methods and approaches were implemented like fencing, placing sign boards, installing sensor alert systems and to reduce these accidents. In this project, a simple and a low-cost approach for automatic animal detection on highways for preventing animal-vehicle collision using computer vision techniques are proposed. The proposed system is trained on more than 2200 images consisting of positive and negatives images and tested on various video clips of animals on highways.

 

Proposed system:

       Proposed system used to detect animals on roadside to avoid animal-vehicle collision, we have trained more than thirty various wildlife animals and each one consists more than 2000 positive and negative images. After training Tensorflow model, it is converted into tflite model to increase the detection speed at lower frame rate.

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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.