Acciona has launched what is billed as an intelligent cloud-based data platform that integrates data to improve the efficiency of water supply management systems.
BIONS (Business Intelligence of Network Solutions) is said to provide a detailed view of water supply services in real time and can shed light on the overall health of the water network.
Thanks to Artificial Intelligence (AI) and Machine Learning (ML) technologies, BIONS is able to not only detect, analyse and manage failures or incidents in the water supply network such as leaks, breaks or faulty assets, it can also predict when they are likely to happen, the statement from Acciona said.
BIONS’ predictive technologies can help prevent water cuts and other system failures before they occur, the firm explained.
“Gulf countries have the lowest per capita renewable freshwater resources in the world, and these are declining rapidly due to population growth. Leaks in the water network are a real challenge in a region that cannot afford to lose water. BIONS can definitely help to improve the efficiency and sustainability of water systems,” said Julio Ratia, O&M Middle East director for Water Solutions at Acciona.
One of the main advantages of this new platform, when integrated with Acciona’s proprietary software GOTA, is the efficiency of the operations and maintenance of the network, with shorter cycles of repair and incident resolution. This can deliver considerable savings to the operator, be they public or private, Ratia added.
Julio de la Rosa, Middle East Business Development director for Water Solutions, explained that BIONS was a key element for preventive operation and maintenance procedures in all its water plants.
The multi-channel platform can be accessed and operated from mobile devices, tablets and personal computers, and features a cybersecurity architecture that protects the system as well as the water network’s data securely in the cloud, the statement noted.
“The technology allows us to know ahead of time what to expect and what will be requested by the plant, allowing us to quickly define the most optimal operational decisions and obtain the most efficient and sustainable output from the facility,” added Rossa.