creator cover Amr El Serougy
Amr El Serougy

Amr El Serougy 

Livestock & Poultry Data Specialist

0subscribers

2posts

goals1
$10.51 of $1 101 raised
I am building smart AI tools to help veterinarians and farmers detect poultry diseases early and make accurate, data-driven diagnostic decisions.

About

Veterinary AI & Data Specialist | Livestock & Poultry Practice
 
I bridge the gap between veterinary medicine and data-driven management for veterinary businesses across Egypt and the Middle East.
 
In a region where maximizing production efficiency and managing operational costs are critical, I empower veterinary enterprises to turn raw data into profitable decisions. Leveraging tools like Power Apps, Excel, Power BI, SQL ,and Salesforce , I help businesses analyze their market performance, automate complex workflows, and streamline their daily operations.
 
By combining my clinical field experience in poultry, sheep, and rabbits with digital transformation strategies, I build practical, scalable tech solutions. My goal is to equip regional veterinary companies with the digital infrastructure they need to automate, innovate, and grow in today's competitive market.
FeedMedia
Aug 31 12:46

Building Smart AI Tools & Hardware for Poultry Health Diagnostics

I am building smart AI tools to help veterinarians and farmers detect poultry diseases early and make accurate, data-driven diagnostic decisions.
In poultry farming, 60% to 70% of disease diagnosis relies on observing clinical signs and post-mortem examination. However, human observation alone cannot continuously track subtle early changes across thousands of birds. My approach combines smart hardware with a Multi-AI diagnostic framework that monitors:
  • Audio & Respiratory Health: Detecting coughs, sneezes, and changes in vocalization in real time.
  • Behavior & Movement: Spotting abnormal posture, depression, decreased activity, puffing up feathers, and loss of appetite.
  • Production & Clinical Signs: Correlating feed/water intake, changes in droppings, egg quality drops, and environmental conditions (CO_2, ammonia, temperature).
Current Phase: Hardware Prototype & Sound AI Model (85,000 RUB)
pdf
AI_livestock_system_for_poultry_production_CC_Licensed_v2.pdf626.40 Kb
  • Hardware & Parts: Sourcing ESP32 boards, microphones, and environmental sensors to build working prototype units.
  • Acoustic AI Training: Recording barn sounds to train on-device AI that distinguishes bird coughs from ventilation and background noise.
  • Field Testing: Running initial barn tests and posting regular milestone reports.
The Bigger Vision: Long-Term R&D for AI in Veterinary Medicine
Reaching this initial goal is the launchpad for a long-term research and development initiative. By merging multi-sensor data (sound, vision, and environment) into an AI Veterinary Assistant System, we can provide veterinarians with objective data to:
  • Make faster, evidence-based field diagnoses.
  • Replace blanket flock treatments with targeted care.
  • Cut unnecessary antibiotic use by up to 70% while improving food safety and flock welfare.
Thank you for supporting this practical step toward the future of digital veterinary medicine!
Should we use AI to help veterinarians detect poultry diseases early through real-time sounds and behavioral signs?
Yes, great idea — It will make diagnosis faster and cut antibiotic overuse.
2 votes
Maybe — I want to see the working prototype first.
No — Traditional checkups and manual inspection are enough.
Other — Sharing my thoughts in the comments.
Oct 13 23:28 · AI content

Smart Respiratory Health Monitoring System for Poultry - Development Update #1

Hello everyone,
I'm excited to share the first development update for my Smart Respiratory Health Monitoring System for Poultry, a project I'm building through ProVetAI.
The goal of this project is to explore how artificial intelligence and embedded systems can help poultry producers identify potential respiratory health issues earlier and support better decision-making in poultry production.
What I've accomplished so far
· Selected and assembled the hardware platform using ESP32.
· Integrated and tested the audio sensing components.
· Successfully captured environmental audio data for analysis.
Subscription levels1

Supporter — 100 ₽ / month

$1.3 per month
Join as an early backer to support the development of innovative AI tools and systems for poultry health diagnostics.
What you get:
- Access to behind-the-scenes prototype build logs and hardware milestones.
- Technical updates on acoustic datasets and on-device AI training.
- Supporter-only polls to help shape future project features.
Go up