November 2025 – Munich, Germany
I competed as a global finalist in Siemens #KicksForEdge, a 72-hour hackathon held at Munich Urban Colab. The event was part of IPCEI-CIS, advancing interoperable cloud–edge technologies.
Hidden faults were buried inside raw PLC logs even when the system reported “OK”. Over 72 hours, we built an edge-based log analytics pipeline to convert unstructured logs into actionable technician insights. Warehouse technicians manually sift through millions of log lines across dozens of PLCs. Unflagged errors cause conveyor arms to misroute packages without triggering alarms. These “silent” failures accumulate into enormous financial loss. Our research showed that Germany alone reported 44,406 operational complaints in 2024 related to delayed/misdirected parcels. (Source included in slide deck)
[12:14:03.112] 'Logger 3 "UNIT-A" (192.168.1.50:5000)' connected!
[12:14:03.129] [COM RECV] RECV STATUS 16#7001
[12:14:03.145] [COM FILL] 01|CV|000101|N|FL|000000//0000|...
[12:14:03.169] [COM RECV] CV|02|000000|A|5|000002//...|SR|...
[12:14:03.332] [COM RECV] CV|02|000000|R|30|000000//...|SR|...
[12:14:03.387] FIFO warning: buffer usage 85%
We built a full pipeline using Node-RED → OpenSearch → Dashboards.
Upload PLC logs (TXT/ZIP) for processing.
Clean + parse raw strings into structured JSON.
Searchable insights + trend views for technicians.
With a unified dataset, the next step is applying Edge AI models to detect anomalies before they become misdirection events. A chatbot interface over OpenSearch gives technicians instant, conversational access to system history and root-cause explanations.