All work

case study

Grade 1.3

Zero-shot forecasting with LLMs

Asking LLMs for the next sensor value, and what I measured

Period
10/2025 – 03/2026
Context
TU Ilmenau, SensBee smart-city platform. Grade 1.3.

Problem

LLMs can forecast without task-specific training. I tested how reliable general-purpose LLMs are on IoT sensor data from the SensBee smart-city platform.

Approach

  • FastAPI microservice for next-value prediction on SensBee.
  • 6-stage data pipeline.
  • 4 LLMs in 192 experiments.
  • Method and results in a written final report.

Results

  • 192 experiments, 4 LLMs.
  • General-purpose LLMs unreliable on numeric sensor data.
  • Grade 1.3.

Worth noting

The negative result is why the thesis benchmarks dedicated time-series models.