{"id":15954,"date":"2025-07-16T16:14:10","date_gmt":"2025-07-16T14:14:10","guid":{"rendered":"https:\/\/blueark.ch\/?p=15954"},"modified":"2025-07-17T07:49:15","modified_gmt":"2025-07-17T05:49:15","slug":"ai-predicts-network-maintenance-needs-and-costs","status":"publish","type":"post","link":"https:\/\/blueark.ch\/de\/ai-predicts-network-maintenance-needs-and-costs\/","title":{"rendered":"AI predicts network maintenance needs and costs"},"content":{"rendered":"\n

Polish utility MPWiK Wroc\u0142aw is using an AI-powered predictive maintenance system to manage its water and sewage infrastructure in collaboration with Amazon Web Services (AWS) and Deloitte.<\/strong><\/p>\n\n\n\n

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One of the challenges modern cities face is that water and sewer infrastructure are often outdated and unable to cope with an expanding population, new housing, new roads, changing and increasing demands from industry, unpredictable weather events, and more.<\/p>\n\n\n\n

Maintaining water and sewer networks, which are often located underground, is a huge challenge, with leaks resulting in huge losses. Although it is hard to calculate an exact figure, it is estimated that a global average of 30 per cent of all fresh water is lost to leaks in pipes<\/a>, with a cost estimate in the hundreds of billions.<\/p>\n\n\n\n

One of the problems associated with these infrastructure challenges is that, historically, it has been very difficult to know what is happening. Leaks are often detected long after they form, and sewer problems are often identified once a serious problem has occurred. Repair costs are also high, with inexact diagnostics and large sections of network to investigate.<\/p>\n\n\n\n

Piotr S\u0142omianny, CIO and CFO, MPWiK Wroc\u0142aw told media: \u201cMPWiK Wroc\u0142aw manages a water supply network of over 2,000 km and thorough rehabilitation of such extensive infrastructure would require almost unlimited financial resources. Given budget constraints, it is important to prioritize the sections that require rehabilitation.\u201d<\/p>\n\n\n\n

He added: \u201cIn view of these challenges, it became necessary to find a tool allowing effective planning for modernisation and achieving the best results with available resources.\u201d<\/p>\n\n\n\n

\"wroclaw-568432_1280_andreas_N_from_Pixabay\"\/<\/figure>\n\n\n\n

Detecting failures before they happen<\/h2>\n\n\n\n

In response to these challenges, MPWiK, in collaboration with Deloitte and AWS as technology partner, decided to implement a predictive maintenance system. The system utilises advanced data analysis and artificial intelligence algorithms<\/a>, along with a detailed understanding of Wroc\u0142aw\u2019s critical water infrastructure.<\/p>\n\n\n\n

The system was developed using a \u2018risk-cause\u2019 analysis, including:<\/p>\n\n\n\n