CMOS VLSI Biosensors and On-Chip VLSI Hardware Accelerators in Health Monitoring

Poultry farming is highly vulnerable to infectious diseases such as Newcastle disease, avian influenza, and coccidiosis, which cause severe economic losses if not detected early. Conventional diagnostic methods are slow, require skilled personnel, and are not scalable for large farms. This paper proposes a real-time poultry health monitoring framework using CMOS VLSI biosensors integrated with on-chip hardware accelerators for acoustic, biochemical, and visual disease detection. A CMOS photodiode array was designed to capture biochemical fluorescence markers with a sensitivity of 92.4% at 10 μM antigen concentration. An NMOS amplifier + band-pass filter front-end processed cough/cluck audio signal, achieving a signal-to-noise ratio (SNR) improvement of 18.7 db. For classification, a hardware CNN-GRU accelerator fabricated in 65 nm CMOS was implemented, consuming 28.6 mW power at 50 MHz clock frequency, while delivering 89.7% detection accuracy across 3 major poultry diseases. Experimental validation on a dataset of 1,200 poultry samples (sound, image, biosensor data) showed an overall disease classification accuracy of 91.3%, a false-positive rate of 4.8%, and an average latency of 1.4 ms per inference. Compared to cloud-based AI, the proposed VLSI system reduced energy consumption by 65% and response time by 72%, enabling continuous on-site monitoring. The proposed CMOS VLSI biosensor and on-chip accelerator framework demonstrates high potential for scalable, low-power, and real-time poultry disease diagnostics. Future work includes integrating wireless transmission and deploying the architecture in farm-scale pilot studies to validate robustness under diverse environmental conditions.