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Project Overview

Electric Motorcycle Monitoring Prototype

A prototype for thinking through telemetry: what should a rider or maintainer see first when performance, usage, and prediction all matter?

July 2025 - September 2025
01Why It Matters

Problem

Telemetry data is only useful when it helps people understand behavior, maintenance needs, and anomalies at the right moment.

For an electric motorcycle, raw measurements such as usage, battery behavior, performance, and operating patterns need to be translated into something a rider or maintainer can act on.

  • A monitoring system can easily become a pile of numbers if the dashboard does not define priority.
  • Riders need fast status awareness, while maintainers need patterns, history, and possible warning signs.
  • The prototype needed to explore predictive analytics without overclaiming production readiness.
02What I Did

Decision

I explored a monitoring prototype with telemetry collection ideas, dashboard sketches, usage patterns, and predictive analytics opportunities.

The work focused on product reasoning: what should be visible first, what belongs in deeper analysis, and what type of signal should trigger action.

  • Mapped possible telemetry inputs from IoT components into dashboard-facing information.
  • Sketched views for usage history, performance summaries, and anomaly-oriented indicators.
  • Used Python, IoT concepts, and web dashboard thinking to connect physical-system data with software workflows.
03What I Learned

Learning & Impact

It expanded my interest in intelligent monitoring systems for physical infrastructure and mobility.

The prototype also helped me connect forecasting, telemetry, and maintenance thinking across different domains, from energy systems to transportation.

  • Built a clearer mental model for telemetry-driven product design.
  • Explored how predictive analytics can support maintenance and operational awareness.
  • Connected IoT data collection with dashboard hierarchy and user decision-making.

Takeaway

The project sharpened my ability to frame raw signals as product questions: what matters first, what can wait, and what should trigger action?

Stack & Links

PythonIoT ComponentsWeb Dashboards
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