Everyone is chasing generative AI and autonomous agents, but the industrial AI that already delivers, predictive maintenance and computer vision, never left the factory floor. A field reality check on hype versus what actually works, and why the best engineering starts with the problem, not the technology.
Barbara´s technology is being implemented for the management and exploitation of energy resources in Local Energy Communities at ELKARTEN Project. It will also secure data exchange of energy generation and consumption amongst their members.
Artificial Intelligence and Machine Learning are the most popular technologies used to create intelligent systems and although they are related, they are not the same. Because of this relationship, when you look at Artificial Intelligence versus Machine Learning, you are actually analyzing their interconnectedness.
Edge Computing enables industrial organizations to make decisions and take action in real-time, reduce latency, improve reliability, enhance security, reduce costs and enable remote monitoring and control. In this article, we explore how Edge Computing is becoming a reference technology for industrial companies that seek to digitize their operations.
The digitization of industry requires interoperability for data sharing and process automation. We delve into how Edge Computing plays a critical role in achieving interoperability by executing data processing at the source, rather than sending it to a centralized location, and at the same time reducing latency, increasing security, and improving the scalability of the system.
Although much of the water infrastructures in place are dozens of years old, in recent times their processes have changed radically thanks to a large extent, to digital technology. Edge computing is one of those technologies that will change the shape of the water industry due to the speed and reliability it provides when modernizing this type of infrastructure.
The rise of Industry 4.0, has brought a sheer amount of data. With the advent of IoT, automation, and advanced analytics, organizations are collecting and generating more data than ever. This data has the potential to revolutionize the way industries operate and improve decision-making. However, with the vast amount of data being generated, its crucial that organizations have the ability to effectively control and manage it.
By controlling data closer to its source and therefore deciding which data needs to be sent to the cloud, the cybersecurity risks of theft or improper access to information are much lower with Edge Computing.
How can the water industry benefit from IoT Edge and AI? IoT is one of the technologies that has made a strong entry into the water industry, developing solutions rich in monitoring, analytical, and automation features. Meanwhile, Artificial intelligence (AI) is making its mark on the water industry, powering intelligent operations using machine learning to optimize resource use and operational budgets for organizations.
In IoT deployments, it is common to hear the term Edge. Many IoT solution vendors, especially in the industrial environment, acknowledge the capabilities of the Edge to generate business value. But what is IoT Edge and what is its relationship with Edge Computing?
