Commence on: 1st November, 2024

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PEST DETECTION IN PADDY

Paddy, a staple crop in Alappuzha, covers vast expanses of the region's fertile land. Just last year, over 27,000 hectares were dedicated to paddy cultivation, yielding an impressive 21,000 tonnes of rice. However, beneath this there's a persistent challenge - the pests that threaten both crop yield and quality. These pests cast a shadow over the livelihoods of countless farmers in the area. Here are some pests that affects the growth of paddy:
• Rice Leaf Folder (Cnaphalocrocis medinalis): Leaf folders are known to fold and damage rice leaves, hindering photosynthesis and nutrient absorption.
• Brown Plant Hopper (Nilaparvata lugens): These sap-feeding insects can transmit plant viruses and weaken rice plants, causing "hopper burn" symptoms that include wilting, yellowing, and reduced panicle development.
• Rice Blast (Pyricularia oryzae): While not an insect pest, rice blast is a fungal disease that affects paddy fields. It causes characteristic blast lesions on leaves, panicles, and stems, resulting in yield loss and grain quality reduction.

Challenge:

In Alappuzha, where the landscape is filled with picturesque rice fields, growing rice is not just a way of life; it's the backbone of survival for numerous farmers. But there’s a problem of pests attacking the crops, reducing the production and quality. Farmers have been found to use some highly toxic pesticides which also kills the enemies of pests as well which is counterproductive.

We Propose:

A Paddy Pest Detection Application that will identify the type of pest affecting the crop by analyzing images of the affected plants. Furthermore, the application will provide crucial insights such as the potential damage level caused by the pest and recommended courses of action, including pesticide selection, avoidance of harmful pesticides, and disease prevention measures.

Our Roadmap:

Week 1

Kick-off Meeting

Discuss project objectives and assign tasks to team members

Week 2

Data Collection

Gather essential data to train our AI model

Week 3 & 4

Data Analysis

Process and prepare the data for model development

Week 5 & 6

Software Implementation

Construct the Paddy Pest Detection Application

Week 7 & 8

Reinforcement and Testing

Rigorously test the software to ensure accuracy and effectiveness

Team Members Needed: 20

By embarking on this endeavor, we aim to empower Alappuzha's rice farmers with a powerful tool to combat pest-related challenges and secure their crops' health and productivity for a prosperous agricultural future.

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