v0.1.0

We’re officially releasing BioBuddy API v0.1.0, a production grade developer interface that exposes the full capabilities of BioBuddy’s Quantum Neural Learning Model (QNL) for seamless integration into third-party applications, IoT devices, and environmental safety systems. This API is built to provide real-time animal detection, classification, and contextual threat assessment using a quantum-inspired hybrid neural architecture optimized for edge performance.

At the core of the API is a lightweight inference engine powered by a QNL model trained on a multi-modal dataset consisting of annotated wildlife imagery, spectrographic audio profiles, and region specific threat metadata. The model architecture combines a ResNet-50 backbone for visual feature extraction with a transformer-based encoder for behavioural pattern recognition and threat level projection. Quantum inspired tensor encodings are used to enhance dimensional representation of uncertainty, allowing the model to maintain high accuracy even under low-signal or noisy conditions.

The API is RESTful, with support for POST endpoints to ingest sensor data in JSON or Base64-encoded image/audio formats. Outputs include species prediction (Top-1 and Top-5), confidence scores, geospatial tagging, and a threat classification index computed through a multi-layer attention mechanism cross-referenced with a regional threat database. Rate limiting, API key authentication, and web hooks for real time alerts are included out of the box. The system supports asynchronous callbacks for batch classification, making it suitable for embedded systems with intermittent connectivity.

BioBuddy API v1.0.0 is fully containerized with a prebuilt Docker image, Swagger documentation, and Python/Node.js SDKs to accelerate adoption. Designed with edge deployments in mind, the model runs efficiently on NVIDIA Jetson modules, Raspberry Pi 4s, and ARM-based microcontrollers with TensorRT or ONNX Runtime acceleration enabled. Use cases include wildlife hazard detection for campers and hikers, ecological monitoring, perimeter safety systems, and intelligent trail companion devices.

This release represents the transition of BioBuddy from a research-grade model to a fully operable developer platform, enabling a new wave of AI powered safety tools for the outdoors.