PROJECT OVERVIEW
Yoli Technologies is developing an advanced AI-powered smart poultry monitoring and predictive intelligence platform designed to transform poultry farming through intelligent sensing, edge computing, and real-time environmental analytics.
The platform combines IoT hardware, artificial intelligence, thermal sensing, and advanced connectivity technologies to help poultry farmers improve productivity, reduce mortality rates, and optimize environmental conditions for maximum yield and animal welfare.
This project reflects Yoli Technologies’ mission to build locally engineered deep-technology solutions that solve real-world African challenges while meeting global technology standards.
THE PROBLEM
Poultry farmers across Africa face major operational challenges, including:
- Poor environmental monitoring inside poultry houses
- Late detection of disease outbreaks
- Inconsistent temperature and humidity control
- Limited predictive production intelligence
- High operational losses due to preventable environmental stress
Most existing solutions are manual, reactive, or rely on expensive imported systems not optimized for African farming conditions.
OUR SOLUTION
The Yoli Smart Poultry Intelligence Platform is a hardware + AI + IoT integrated system that continuously monitors farm conditions and predicts risks before they translate into production losses.
Smart Environmental Sensing
Custom-designed IoT hardware nodes deployed inside poultry houses monitor:
- Temperature distribution across zones
- Humidity levels
- Air quality and ventilation behavior
- Poultry activity and behavior patterns
- Thermal stress indicators using intelligent thermal sensing
The hardware is engineered for harsh farm environments, low power consumption, and long-term operational reliability.
Edge Artificial Intelligence Processing
The platform uses edge computing to process environmental data locally, enabling:
- Real-time anomaly detection
- Early disease and stress risk prediction
- Reduced bandwidth and cloud dependency
- Faster alert generation for farm operators
Predictive Poultry Intelligence
Machine learning models analyze environmental and operational data to:
- Predict egg production trends
- Detect early disease outbreak indicators
- Recommend environmental adjustments
- Optimize feeding and ventilation schedules
Connectivity and Remote Farm Visibility
The system supports multiple connectivity layers:
- Wi-Fi and Ethernet infrastructure
- Future cellular IoT integration
- Secure device-to-cloud data transmission
- Remote monitoring dashboards and analytics interfaces
SYSTEM ARCHITECTURE OVERVIEW
The Yoli Smart Poultry Intelligence Platform is built on a layered architecture combining intelligent sensing hardware, edge artificial intelligence processing, secure connectivity, and scalable cloud analytics.
Intelligent Sensing Layer (Farm Environment Layer)
Distributed smart IoT sensing nodes deployed across poultry housing zones provide continuous environmental data capture and monitoring across multiple parameters.
Edge Intelligence Layer (On-Site Processing)
Edge computing modules process sensor data locally for anomaly detection, preprocessing, and alert generation while reducing bandwidth usage.
Connectivity and Data Transport Layer
Ensures secure and reliable data transmission between farm systems and cloud infrastructure through Wi-Fi, Ethernet, and future cellular IoT integration.
Cloud Intelligence and Analytics Layer
Handles long-term storage, machine learning optimization, predictive analytics, and cross-farm intelligence.
Application and User Interface Layer
Provides dashboards, alerts, and monitoring tools for farm managers.
DEPLOYMENT ROADMAP
Yoli Technologies is executing a phased deployment strategy to ensure technical reliability, validated agricultural impact, and scalable commercial rollout across Africa.
Phase 1: Prototype Development and Laboratory Validation (Completed / Ongoing)
Phase 2: Pilot Deployment – University of Buea (2026)
Phase 3: Early Commercial Deployment – Regional Farms (2026–2027)
Phase 4: National Scale Deployment – Cameroon (2027–2028)
Phase 5: Pan-African Expansion (2028 and Beyond)
ACADEMIC MENTORSHIP AND RESEARCH COLLABORATION
Professor Michael Ekonde Sone — University of Buea
Dr. Ewane Divine — University of Buea
PILOT ENVIRONMENT: UNIVERSITY OF BUEA
The University of Buea serves as the pilot environment for early validation and testing, enabling real-world environmental data collection, AI validation, hardware testing, and continuous expert feedback.
IMPACT AND VALUE CREATION
The platform is designed to support reduced poultry mortality, increased farmer productivity, improved food production stability, and data-driven agriculture transformation in Africa.
VISION
Yoli Technologies aims to become a leader in African-built deep-technology solutions for agriculture, industrial monitoring, and smart infrastructure.
ABOUT YOLI TECHNOLOGIES
Yoli Technologies is a telecommunications, networking, and intelligent systems engineering company delivering next-generation technology solutions across Africa, including IoT systems, AI-driven monitoring platforms, smart infrastructure, and advanced connectivity solutions.
