SAMTEH: A Smart Adaptive Micro-Turbine Energy Harvester for Intelligent Airflow-Based Power Generation

<ns3:p>Background Airflow based micro-energy harvesting has emerged as a solution for powering autonomous embedded and IoT systems in ducted environments such as HVAC systems and industrial exhaust systems. However existing technology focuses on mechanical optimization, lacking in adaptive electrical control and protection. Methods This paper proposes the Smart Adaptive Micro-Turbine Energy Harvester, an airflow driven energy harvesting system integrating real time voltage and current sensing, embedded control logic and relay-based load modulation. The system operates through multiple modes including Harvest mode, Limit mode and Protection mode to regulate electrical behavior under varying airflow conditions. Experimental testing under low, moderate, high and very high airflow conditions demonstrated stable voltage generation, adaptive load regulation, reduced voltage fluctuations and improved operational safety. Results The system efficiently transitioned between different operational modes in response to varying airflow conditions and electrical loading. Experimental results also showed improved operational stability and protection against excessive voltage conditions. Conclusion SAMTEH demonstrates the feasibility of integrating adaptive control and protection-oriented regulation into airflow based micro-energy harvesting systems. The proposed architecture improves system reliability and operational stability, making it suitable for intelligent IoT and industrial energy harvesting applications.</ns3:p>

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Publication Details

Journal
F1000Research
Published
2026-06-09
DOI
https://doi.org/10.12688/f1000research.182056.1
Primary Topic
Innovative Energy Harvesting Technologies
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article
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article

SAMTEH: A Smart Adaptive Micro-Turbine Energy Harvester for Intelligent Airflow-Based Power Generation

Sharik Ahmad, Shahnawaz Ali, Syed Arshad Ali, Craig Karichi
F1000Research
Innovative Energy Harvesting Technologies
article

SAMTEH: A Smart Adaptive Micro-Turbine Energy Harvester for Intelligent Airflow-Based Power Generation

Sharik Ahmad, Shahnawaz Ali, Syed Arshad Ali, Craig Karichi
article en

Abstract

<ns3:p>Background Airflow based micro-energy harvesting has emerged as a solution for powering autonomous embedded and IoT systems in ducted environments such as HVAC systems and industrial exhaust systems. However existing technology focuses on mechanical optimization, lacking in adaptive electrical control and protection. Methods This paper proposes the Smart Adaptive Micro-Turbine Energy Harvester, an airflow driven energy harvesting system integrating real time voltage and current sensing, embedded control logic and relay-based load modulation. The system operates through multiple modes including Harvest mode, Limit mode and Protection mode to regulate electrical behavior under varying airflow conditions. Experimental testing under low, moderate, high and very high airflow conditions demonstrated stable voltage generation, adaptive load regulation, reduced voltage fluctuations and improved operational safety. Results The system efficiently transitioned between different operational modes in response to varying airflow conditions and electrical loading. Experimental results also showed improved operational stability and protection against excessive voltage conditions. Conclusion SAMTEH demonstrates the feasibility of integrating adaptive control and protection-oriented regulation into airflow based micro-energy harvesting systems. The proposed architecture improves system reliability and operational stability, making it suitable for intelligent IoT and industrial energy harvesting applications.</ns3:p>

F1000ResearchVol. 15
Technical University of Malaysia Malacca (MY), Sharda University (IN)
Affordable and clean energy
Openalex Percentile: Top 11%
Innovative Energy Harvesting Technologies
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SAMTEH: A Smart Adaptive Micro-Turbine Energy Harvester for Intelligent Airflow-Based Power Generation — Sharik Ahmad, Shahnawaz Ali, et al. · F1000Research (2026) | TGRS Research Map | TGRS