Applying AI to real-time IoT data
brings prompts advantages for companies, like considerable reductions in energy and raw material waste. The alarming worldwide and Europe’s current energy market situation is quite clear to everyone. According to a report by Allianz, the invasion of Ukraine will propel Europe’s already high energy prices even higher; indeed, they expect at least a 30% increase in the energy bill for 2022.
Moving to environmental aspects, reducing the overall carbon footprint impact is one of the EU’s sustainable goals within 2030. This is the reason why so many companies struggle to find the most suitable solutions to cut costs and reduce CO2 impacts on the Planet.
The importance of sensors and AI
Here they come sensors, that completely changed how we capture data – offering a proper tool to plan future actions and drive more efficient performances. Indeed, the better the monitoring and measuring data, the better one can understand a company’s data history and potential use cases for reliable future decision-making actions. For instance, through sensors data, we can easily detect factories’ total energy use, how much power lighting, heating, cooling equipment and systems consume, and so on. Therefore, keeping data from sensors under control is worthwhile for any manufacturing industry.
Disaster detection and Early Warning systems are priceless in such sectors. They can forecast anomalies that might be harmful. This will provide some time for the response system to prepare for adverse events and lower their impact. And Artificial intelligence is the most suitable solution here.
Thanks to AI and Machine Learning integration, data analysis has been employed to optimise industrial processes and, as a result, to reduce waste and energy consumption in energy-intensive sectors – such as manufacturing. Hence, energy efficiency can be achieved through regular data stream monitoring.
Here comes Radicalbit’s latest product, Helicon, a platform designed to combine real-time data processing with AI. Employing Artificial Intelligence on industrial devices’ data flow, Helicon can properly provide an Early Warning system to limit the possible negative impacts of irregular production processes. This method allows saving up to 40% of production energy resources. If the cost-per-unit ratio improves, the process becomes more sustainable. As a result, a company would be less exposed to fluctuations in energy costs.
How Helicon works in IoT
As a concrete example, we employed Helicon to process IoT data of a chemical factory. The goal here was to detect process anomalies in real-time. The system offered a critical set of information, allowing technical personnel to quickly intervene during the process. This mitigated and avoided any negative impact (like energy and raw material waste).
Applying AI to real-time IoT data – we could say in a dynamic way – brings prompt advantages; in machines using tools subject to wear Helicon was able to intercept anomalies as they were occurring. This dynamic approach raised the instrument’s life expectancy by 30%, just using tools until the very end of their natural life.
How AI can help Agritech with data-driven water management
Climate change has been receiving growing attention in the last few years, with more and more people concerned about the human contribution to global warming. An aspect of climate change that is already affecting numerous countries and causing great distress is the...
How Streaming ML saved Christmas: a Helicon use case for Santa’s delivery optimization
Scenario & Challenge Christmas is no joke, especially for Santa Claus. Each year Father Christmas has only one night to deliver gifts to the entire world population, which in 2022 reached 8 billion people. Even considering only children and young people under 18,...
How IoT and AI can increase energy efficiency for large buildings
In this blogpost we put forward an innovative solution to prevent energy waste in sizable buildings such as office blocks and dorms. In these indoor environments, energy waste often arises when lighting, heating or electric appliances are inadvertently left on in...