Your browser does not support JavaScript! Please enable the settings.

Electursys- Industrial IoT & AI based Predictive Maintenance Solution


Karsten Moholt




An R&D project funded by Eureka and Innovate UK. Developed in collaboration with Karsten Moholt. Karsten Moholt is a specialist operator and maintenance provider for Offshore infrastructures like Oil & Gas rigs, wind turbines and more


  • Collect data points & build models to predict electrical component failures on Wind Turbines, so that the system can automatically schedule preventive maintenance.
  • Providing reliable and consistent connectivity in various environments, including remote or harsh conditions.
  • Handling the vast amounts of data generated by IoT devices requires efficient storage, processing, and analysis capabilities to derive actionable insights.
  • Ensuring seamless integration and communication between diverse devices and platforms with different standards and protocols is a significant challenge.
  • Protecting sensitive data and ensuring privacy are major concerns due to the increased number of connected devices, which can be vulnerable to cyber-attacks.
  • Managing the growth of IoT networks, which may involve thousands or millions of devices, requires scalable solutions for data processing, storage, and communication.

Key Objectives

  • To create a web-based solution that can be integrated with wind turbines to pull relevant data for predicting electrical failures,
  • Execute technical R&D to understand data patterns that can help predict electrical component failures.



We created a comprehensive data model capable of predicting failures. In a wind turbine with over 10,000 components, our data model predicts both mechanical and electrical failures. It specifically forecasts when electrical failures may occur.

We developed a network architecture to collect various sensor data, created APIs for real-time data collection, implemented pre-processing to minimize latency, developed AI algorithms to predict faults, designed a UI to visualize data trends, and created a scheduling system for maintenance.

Technology used

nodejs-2 python react-5 aws-76fcbf94cc11 lorawan-devices-sensors-2


cite icon
A full suite of products to collect data, process data, predict faults, electric failures and schedule maintenance automatically.

Related Case Study

Let's discuss your project today