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At Roedan, we pride ourselves on our ability to address complex engineering challenges with technical knowledge and precision. One such challenge arose recently, when a long-standing client approached us with concerns about the accuracy and quality of data from their low-power, accelerometer-based device. 

(Scorpion data logger box) 

The client’s device, while compact, offered limited access to raw sensor data. To investigate without disrupting the normal operation of the device, we introduced additional analytics and telemetry. These were designed to observe and log behavior discreetly, ensuring no interference with its existing functionality. 

Leveraging our Scorpion Platform, a component of the broader Roedan Sensor Fusion Platform, we deployed a battery-powered companion device. This hardware was capable of operating in parallel with the client’s solution, capturing high-resolution data independently and at significantly higher sample rates and accuracy. 

To support deployment, we also developed a brand-new companion mobile application, built from the ground up to provide basic control of the Scorpion system. The app enables quick configuration and operation directly from a smartphone. 

(APP screenshot) 

Over the course of several days, we collected data from both the Scorpion unit and the client’s device. Our engineering team then conducted a comparative analysis. While the Scorpion data offered rich insight into device dynamics, it also helped highlight discrepancies in the mathematical modelling used within the client’s original implementation. 

(Applying filtering and analysing cornering data over a small window)

By examining these inconsistencies, we were able to identify the root cause and promptly develop revised algorithms that preserved the client’s original design intent but improved accuracy. These algorithms are now undergoing field trials, running concurrently on both the client’s hardware and our Scorpion system for performance assessment. 

All core development including the Scorpion firmware adjustments and the mobile app were turned around within a day to allow the real work of analysing data to be started straight away. This allowed us to rapidly prototype, adapt existing systems, and deploy targeted solutions to meet client requirements swiftly and effectively.