Energy harvesting technologies and machine learning have wide applications in energy infrastructures and offer solutions in reducing maintenance costs, offering potential solutions in autonomous maintenance. These topics along with case studies in structural health monitoring and power distribution will be covered in this course. Read more Read less

This course will cover two key technologies used in the advancement of autonomous maintenance in energy infrastructures.

Energy harvesting is used in IoT (Internet of Things) and WSN (Wireless Sensor Network) to power sensors and communication devices by harvesting ambient energy (e.g., vibration, heat, etc.) to achieve autonomous monitoring of infrastructures.

Machine learning, used alongside IoT and WSN, is to analyse the data collected by the sensors to accurately inform events that have happened or predict events that might happen in the infrastructures. These technologies are keys in the advancements of smart technologies that could significantly reduce the maintenance costs of infrastructures.

At a glance

  • Dates
    • Please enquire for course dates
  • Duration6 hours over 3 days
  • LocationOnline
  • Cost£250 Concessions available

Course structure

The course is delivered online over 3 days, 2 hours per day

What you will learn

By attending the course, you will learn about the technologies which could potentially reduce the maintenance costs via autonomous monitoring. This is useful in energy infrastructures particularly renewable energy where maintenance attributes a large portion in the project costs. They also provide other benefits include providing early warning to prevent catastrophic failures, monitoring in remote areas, assisting in optimisation of the design and performance of the infrastructures.   

Core content

  • Mechanical energy harvesting,
  • Thermal energy harvesting,
  • Case study of energy harvesting in structural health monitoring,
  • Machine learning in data analysis,
  • Case study of machine learning in energy and structural health monitoring.

Who should attend

  • Those involved in the maintenance of energy infrastructures, e.g., wind turbines, power grid, oil pipelines, etc.
  • Those involved in the design of renewable energy infrastructures,
  • Those involved in the research and development of IoT and WSN.


Discounts are available for multiple bookings.

Read our Professional development (CPD) booking conditions.