With over 126 million cubic meters of water wasted worldwide annually, industrial IoT could be an effective solution for smart water management to reduce economic and environmental costs, wrote Vernon Turner, Product Marketing Manager, IoT Edge & Data, Cisco Internet of Things (IoT).
IoT technology can leverage sensors to be a viable solution that oversees and preserves the physical infrastructure in real-time and ensures water safety and sustainability. IoT sensors can keep track of water levels and collect data for analysis, they can identify pipe leaks, oversee health and safety metrics and help establish further requirements.
Unlike condensed environments such as factory floors, water utilities bring in challenges unique to distributed environments due to a large physical footprint which includes assets such as reservoirs, pipes, and pumps. Such infrastructures introduce high costs due to data being time-sensitive and any delay in its move to the cloud could result in overloading costs.
Edge computing and data analysis at the edge could be the answer, Turner said, as data would no longer have to first be captured and moved, it would instead be processed at the network edge.
“Utilities could establish clear policies to trigger appropriate responses – for example, to shut off a valve when a reservoir level falls below a certain threshold or to alert when flow capacity is off, suggesting the presence of a leakage that should be addressed,” he explained.
An industrial IoT network can leverage edge intelligence to provide real-time, cost-effective and smart analytics for large-scale water infrastructures.
Kubota migrates infrastructure to Microsoft Azure cloud
Tractor and heavy equipment manufacturer Kubota entered a multi-year partnership with Microsoft last month to migrate it’s IT infrastructure and SAP mission-critical systems to Microsoft Azure’s cloud platform.
As part of its digital transformation program and sustainability efforts, Kubota is making the move to a solution provision model and will develop solutions for organizations in critical sectors such as food, water and the environment with Microsoft’s AI technologies.
Kubota and Microsoft will leverage each other’s expertise and technology to address global food demands and field management challenges. By modernizing its IT infrastructure, Kubota can use AI technologies to scale its business, streamline operations and speed up the global use of integrated data.
“Under the slogan of ‘For Earth, For Life,’ Kubota is trying to dedicate to solve global issues on food, water, and environment,” said Yuichi Kitao, President and Representative Director, Kubota, in a prepared statement. “It is indispensable to promote digital transformation to meet such issues worldwide. This alliance with Microsoft is an important step for the digital transformation. We accelerate to create innovations and provide the solutions and the social value.”
Kubota and Microsoft are also launching an AI Machine Learning Lab to train new developers building AI solutions and explore AI use cases in agriculture, water system infrastructure and the environment.
“Kubota is recognized as a leader in environmentally-compatible farming and agricultural equipment,” said Judson Althoff, Executive Vice President, Microsoft, in a prepared statement. “Combining its deep industry experience with the power of Microsoft Azure and AI capabilities will enable delivery of new innovations that help feed a hungry planet, ensure access to clean water, and promote overall sustainability.”
There is a lot of use for AI within agriculture and water systems. Utilities were an early use case for Big Data and AI with electricity using the technologies to manage demand and detect unusual (ie. fraudulent) usage. Manufacturing is traditionally a vertical that spends little on IT and technology outside its core business, but now traditional companies are coming to see cloud and AI as a way of automating core functions while driving intelligence, and building new product offerings.
Daniel Beazer, Senior Contributing Analyst, Structure Research
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