Pigeon Pulse
Intelligent Avian Health Monitoring System
Smart health-monitoring ecosystem for pigeons using lightweight IoT devices to track vitals, detect early symptoms of illness, and enable real-time care decisions in large aviaries.
Timeline
6-8 months
Team Size
4-6 engineers
Technologies Used
The Challenge
Pigeon caretakers in large aviaries faced a critical problem: detecting illness early enough to save birds. Traditional methods relied on manual observation—inconsistent, time-consuming, and often too late.
There was no digital system in place. Everything was logged manually, observations were spotty, and by the time symptoms became visible, disease had often spread throughout the flock.
Our Mission
We set out to automate health tracking, identify anomalies early, and give caretakers real-time visibility into the health status of every bird.
What We Delivered
Pain Points & Challenges
Tiny Sensors for Tiny Birds
Designing ultra-lightweight, non-invasive IoT sensors that pigeons could wear comfortably was a major engineering constraint.
Erratic Connectivity
Aviaries presented challenging RF environments with signal drop-offs and interference from building structures.
Battery Life Issues
Continuous monitoring drained batteries quickly, requiring innovative power management solutions.
No Historical Datasets
Lack of existing health data for training anomaly detection models made baseline creation difficult.
How We Overcame Them
Aggressive Power Management
Designed custom firmware with advanced sleep modes and wake-on-motion protocols to extend battery life by 300%.
Edge Filtering
Implemented intelligent edge computing to filter and compress data at the source, minimizing packets sent to the cloud.
RF Optimization
Strategically placed RF repeaters and optimized antenna placement to eliminate connectivity dead zones.
Crowdsourced Baseline Model
Created a pseudo-baseline health model using aggregated data from multiple aviaries to establish normal ranges.
Results & Impact
40-60% improvement in disease detection time
70% reduction in manual monitoring workload
Higher survival rates through early intervention
Predictable care cycles and resource allocation
Real-time visibility for caretakers across multiple locations
"The client reported higher survival rates and more predictable care cycles, transforming how they manage aviary health."
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