Sternum Continuous Monitoring is a cloud-based IoT observability and monitoring platform that collects device and fleet-level telemetry data to support issue detection, root cause analysis, and operational visibility for IoT device manufacturers and developers. Data collection is facilitated by a lightweight Observability SDK written in C and optimized for embedded systems. The SDK functions as an abstraction layer between IoT devices and the cloud platform, supporting any device type, OS, or communication stack (including Bluetooth, BLE, MQTT, and WiFi). It can also act as a proxy for isolated IoT systems. The platform ingests software signals (status and error codes) as well as hardware diagnostics (temperature, voltage, pressure readings) and custom trace data (CPU/memory utilization, network stats, battery levels, RSSI, and more). Key capabilities include: - Adaptive anomaly detection using multivariate AI analysis of software and hardware metrics, which automatically learns device routines upon connection. - Contextual root cause analysis with detailed event chronologies and visual timelines for each alert. - Early issue discovery that correlates trace data with failed tests, specific lines of code, process IDs, or memory locations. Integrates with the EIV™ technology to detect code and memory bugs (e.g., memory leaks, invalid commands) in preproduction. - Customizable dashboards, views, and alert conditions (string matches, event counts, occurrences over time). - Fleet management with a bird's-eye view of device profiles, firmware versions, deployment status, locations, connectivity, and error trends across large device inventories.