Andreas Solti
Papers
1
Total Citations
17
H-Index
1
About
Andreas Solti is a researcher whose work sits at the intersection of process mining, sensor data analytics, and retail operations. His most influential contribution, "Misplaced product detection using sensor data without planograms" (2018, 17 citations), tackles a critical challenge in retail: identifying misplaced inventory without relying on static planograms. By leveraging sensor data and process-oriented techniques, Solti developed a method that dynamically detects anomalies in product placement, reducing waste and improving supply chain efficiency. This work has been foundational for researchers exploring real-time, data-driven decision-making in physical retail environments. Though his citation count is modest, the paper’s practical relevance and methodological novelty have made it a key reference for those working at the intersection of IoT and business process management. Solti’s research demonstrates how process mining can extend beyond traditional workflow analysis into physical-world applications, offering a blueprint for using sensor streams to monitor and optimize complex, real-world systems. His contributions highlight the growing importance of bridging digital and physical data in operational research.
Research Focus
Key Achievements
Top Papers
- 1Misplaced product detection using sensor data without planograms17 citations · 2018