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Related Experiment Videos

End-to-end IoT sensor data simulation and predictive analysis: framework implementation and experimental evaluation.

Darlan Noetzold1, Valderi Reis Quietinho Leithardt2, Juan Francisco de Paz3

  • 1Expert Systems and Applications Laboratory (ESALAB), Faculty of Science, University of Salamanca, Salamanca, Spain. darlannoetzold@usal.es.

Scientific Reports
|May 18, 2026
PubMed
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This summary is machine-generated.

SHiELD optimizes Internet of Things (IoT) sensor data using heuristics and predictive models. This platform reduces data volume and transmission, enhancing system reliability for efficient IoT data management.

Area of Science:

  • Computer Science
  • Data Science
  • Network Engineering

Background:

  • The Internet of Things (IoT) generates vast amounts of sensor data, posing challenges for efficient management and transmission.
  • Existing methods often struggle to balance data fidelity with reduced data volume and transmission overhead.

Purpose of the Study:

  • To introduce SHiELD, a comprehensive platform for simulating, predicting, and assessing the reliability of IoT sensor data streams.
  • To evaluate the effectiveness of heuristic techniques and advanced predictive models in managing sensor data.

Main Methods:

  • Implemented heuristic techniques: aggregation, compression, and filtering for data streamlining.
  • Integrated advanced predictive models: ARIMA, LSTM, and Transformer architectures for forecasting.
Keywords:
Heuristic optimizationIoT data simulationMachine learningPredictive analyticsSimulator

Related Experiment Videos

  • Incorporated fault injection for system robustness evaluation and reliability assessments using time-series similarity, recovery performance, and transmission quality metrics.

    • Main Results:

    • SHiELD's heuristics reduced data volume by an average of 9.4% (8.3%–13.5%) and decreased packet transmission counts by up to 82.5%.
    • Predictive models achieved high performance, with F1-scores up to 0.93 and ROC AUC values up to 0.97 (Transformer, Prophet).
    • Validation experiments using real-world data confirmed the platform's effectiveness on embedded and server platforms.

    Conclusions:

    • SHiELD provides an integrated framework for effective IoT sensor data simulation and reliability assessment.
    • The platform successfully balances data fidelity with significant reductions in data volume and transmission.
    • SHiELD enhances the robustness and efficiency of IoT systems through advanced data management techniques.