Meeting Log 03: Asynchronous Data Ingestion and Latency Mitigation
Serial Buffer Saturation and Real-Time Algorithmic Optimization
Meeting Details
Date: 03 March 2026
Attendees: Ketan Clint Pinto, Mr. Roshan Renji
Subject: Serial Buffer Saturation and Real-Time Algorithmic Optimization
By the third supervisory session, the physical hardware array and the initial Python data-parsing scripts had been successfully integrated. However, performance benchmarking revealed a severe asynchronous latency issue. During simulated fall events, the system exhibited a delayed response time exceeding 15 seconds. The supervisor conducted a code review and identified a critical data ingestion bottleneck. The Raspberry Pi 5 was receiving 64 complex subcarriers at 10 frames per second, but the Python engine's NumPy matrix calculations could not process the arrays synchronously. This discrepancy resulted in a massive queue of unread bytes accumulating within the USB serial buffer, forcing the system to analyze heavily outdated telemetry during real-time emergencies.
To rectify this, the supervisor mandated the implementation of a strict queue-flushing protocol within the serial listener thread. The software was updated to continuously monitor the in_waiting buffer metric. A logical failsafe was introduced: should the queue exceed 2,000 bytes, the script automatically executes a reset_input_buffer() command. This mechanism instantaneously purges obsolete data, ensuring the mathematical engine consistently evaluates the most recent physical frame. Concurrently, the detection mathematics were refined. The flawed raw amplitude thresholding method was discarded in favour of a "Wave-Shift" algorithm, which calculates standard deviation across a rolling 10-frame buffer to dynamically filter ambient thermal noise. Subsequent testing demonstrated that these optimizations successfully reduced system latency to sub-500 milliseconds.