Multi-Sensor Calibration Planning in IoT-Enabled Smart Spaces

摘要: Emerging applications in smart cities and communities require massive IoT deployments using sensors/actuators (things) that can enhance citizens' quality of life public safety. However, budget constraints often lead to limited instrumentation and/or the use low-cost sensors are subject drift bias. This raises concerns robustness accuracy decisions made on uncertain data. To enable effective decision-making while fully exploiting potential sensors, we propose send mobile units (e.g., trained personnel) equipped with high-quality (more expensive) freshly-calibrated reference so as carry out calibration field. We design implement an efficient cooperative approach solve planning problem, which aims at minimizing cost recurring multiple sensor types long-term operation. a two-phase solution consists selection phase minimizes average calibration, path travel calibrators have load constraints. provide fast heuristics for both phases. further build prototype facilitates mapping deployment field provides navigation guidance calibrators. Extensive use-case-driven simulations show our proposed significantly reduces compared naive approaches: up 30% moderate-sized indoor case, higher outdoor cases depending scale.