Blockchain-Driven IoT Ecosystem for Next-Level Poultry Management ppt.pptx

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1. BRINDAVAN INSTITUTE OF TECHNOLOGY & SCIENCE (BITS-KNL) (Approved by AICTE &Affiliated to JNTUA, Anantapur, A.P.) NH-7, PEDDATEKUR, KURNOOL-518218 A Project Review on "Blockchain-Driven IoT Ecosystem for Next-Level Poultry Management" Presented by TECH TITANS Names Roll Numbers GOPIREDDY DEEPTHI 212N1A0523 JANGAM SHIVALEELA 212N1A0526 MANGALURU JYOTHSNA 212N1A0535 EDIGA RAKESH GOUD 212N1A0518 Guide Name Head of the Department Mr.S. Abdul Yunus Basha Mr.S.Srihari Reddy Assistant Professor Assistant Professor Department of CSE Department of CSE

2. Blockchain-Driven IoT Ecosystem for Next-Level Poultry Management An Innovative Approach for Smart Poultry Farming

3. Abstract The current poultry management system relies on manual processes with limited automation, monitoring, and data security. Most farms lack AI, IoT, and blockchain integration, leading to inefficiencies, high operational costs, and a lack of transparency in industry-to-industry transactions This “Blockchain-Driven IoT Ecosystem for Next-Level Poultry Management” integrates IoT, AI, and Blockchain for real-time monitoring, automation, and data security. IoT sensors (DHT11, ultrasonic, MQ-135, load cells) track temperature, humidity, feed, water levels, gas, weight and chicken health. Blockchain ensures secure, tamper-proof transaction records for industry-to-industry data sharing. AI analyzes egg quality, farm cleanliness, and detects harmful conditions. It also monitors chicken health using image processing, Convolution Neural Networks and behavior tracking to detect diseases. Automation optimizes feeding, climate control using Rule Based Threshold System and alerts for abnormal conditions using Blynk. An AI-powered dashboard provides real-time analytics for farm management.

4. Objectives IoT for Monitoring: Sensors such as DHT11 (temperature & humidity), ultrasonic sensors (feed & water level), MQ-135 (gas detection), load cells (weight monitoring), and cameras collect real-time farm data. An LCD display provides on-site monitoring. Blockchain for Secure Data Storage: Ensures tamper-proof transaction records for industry-to-industry (B2B) data sharing, improving traceability. AI for Analysis & Automation: Convolutional Neural Networks (CNN): Used for egg quality classification (good vs. bad eggs) and detecting cleanliness issues using image processing . Chicken Health Monitoring: AI analyzes weight, behavior, movement and image data to detect diseases and abnormal conditions. Predictive Analytics: AI forecasts potential health risks based on sensor trends. Automation & Alerts: Automated Feeding & Climate Control based on sensor data using Rule Based Threshold System(IF-ELSE logic). Instant Alerts for extreme temperature, gas leaks, low feed/water levels, and potential diseases using B lynk. AI-Powered Dashboard: Provides real-time analytics, health reports for better decision-making.

5. Literature Review 5 “ IoT Based Smart Automated Poultry Farm Management System ” by Bharati Ramteke and Snehlata Dongre on June 2022 . “Cloud-Based IoT Solution for Enhanced Poultry Farm Management” by M Venakata sai prasad, A Sumalatha on June 2024. “An IoT and ML-based Poultry Waste Management System” by R O Aashvina, S Monika on February 2023. “Prototyping an IoT -Based Smart Controlled Poultry Farm System” by Indra Hartarto Tambunan, Noel Riki Apryanto on December 2024.

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