BrainBox’s AI-powered autonomous buildings come to UK
BrainBox AI has launched its artificial intelligence-led system for buildings in the UK and Ireland.
The technology, which focuses on increasing efficiency in heating, ventilation and air conditioning (HVAC) systems, comes to 10 buildings at launch, comprising over a million square foot of commercial estates across the two nations.
BrainBox AI uses deep learning and cloud-based computing to predict a building’s thermal load, allowing for round-the-clock self-operation of comfort facilities. The systems operate autonomously in real time, which the company claims can lead to savings of up to 25 percent in as little as three months. The savings are twinned with increased carbon efficiency (with a reduction of 20-40 percent) and a 60 percent increase in ‘occupant comfort’.
Sam Ramadori, chief operating officer of BrainBox AI, said, “Heating and cooling represent 45% of the energy used in commercial real estate and traditional HVAC systems are reaching the limit of how that use can be optimised. With cost control and environmental concerns at an all-time high, we need to embrace new ways of reducing the energy footprint that commercial real estate has. It is exciting to see how autonomous artificial intelligence is creating entirely new approaches to delivering material energy savings. Expanding into the UK and Ireland will allow BrainBox AI to help more real estate operators better manage building energy consumption and costs.”
The Canadian company first expanded into the US before making a push into European and APAC expansion.
Google launches Visual Inspection AI tool for manufacturers
Google Cloud has launched Visual Inspection AI, a new tool to help manufacturers identify defects in products before they're shipped.
Poor production quality control often leads to significant operational and financial costs. The American Society for Quality estimates that for many organisations this cost of quality is as high as 15-20% of annual sales revenue, or billions of dollars annually for larger manufacturers. Google Cloud’s new Visual Inspection AI solution has been purpose-built for the industry to solve this problem at production scale.
How does it work?
The Google Cloud Visual Inspection AI solution automates visual inspection tasks using a set of AI and computer vision technologies that enable manufacturers to transform quality control processes by automatically detecting product defects.
Google built Visual Inspection AI to meet the needs of quality, test, manufacturing, and process engineers who are experts in their domain, but not in AI.
- Run autonomously on-premises: Manufacturers can run inspection models at the network edge or on-premises. The inspection can run either in Google Cloud or fully autonomous on your factory shop floor.
- Short time-to-value: Customers can deploy in weeks, not the months typical of traditional machine learning (ML) solutions. Built for process and quality engineers, no computer vision or ML experience required. An interactive user interface guides users through all the steps.
- Superior computer vision and AI technology: In production trials, Visual Inspection AI customers improved accuracy by up to 10x compared with general-purpose ML approaches, according to benchmarks from several Google Cloud customers.
- Get started quickly, with little effort: Visual Inspection AI can build accurate models with up to 300x fewer human-labeled images than general-purpose ML platforms, based on pilots run by several Google Cloud customers.
- Highly scalable deployment: Manufacturers can flexibly deploy and manage the lifecycle of ML models, scaling the solution across production lines and factories.
Industry use cases
The demo video shows how Visual Inspection AI addresses use cases to solve specific quality control problems in industries such as automotive manufacturing, semiconductor manufacturing, electronics manufacturing and general-purpose manufacturing.
Kyocera Communications Systems, a manufacturer of mobile phones for wireless service providers, has been able to scale its AI and ML expertise through the use of the solution. “With the shortage of AI engineers, Visual Inspection AI is an innovative service that can be used by non-AI engineers,” said Masaharu Akieda, Division Manager, Digital Solution Division, KYOCERA Communication Systems. “We have found that we are able to create highly accurate models with as few as 10-20 defective images with Visual Inspection AI. We will continue to strengthen our partnership with Google to develop solutions that will lead our customers' digital transformation projects to success.”
Visual Inspection AI has fully integrated with Google Cloud's portfolio of analytics and ML/AI solutions, giving manufacturers the ability to combine its insights with other data sources. The tool integrates with existing products from Google Cloud partners, including SOTEC, Siemens, GFT, QuantiPhi, Kyocer and Accenture.