{"id":2277,"date":"2024-12-13T11:00:35","date_gmt":"2024-12-13T14:00:35","guid":{"rendered":"https:\/\/paipe.com\/?p=2277"},"modified":"2026-09-10T11:59:51","modified_gmt":"2026-09-10T14:59:51","slug":"ai-applied-to-iot-networks-how-to-predict-failures-in-transmission-towers-before-they-affect-operation","status":"publish","type":"post","link":"https:\/\/paipe.com\/en\/blog\/inteligencia-artificial\/ia-aplicada-a-redes-iot-como-prever-falhas-em-torres-de-transmissao-antes-que-afetem-a-operacao","title":{"rendered":"AI applied to IoT networks: how to predict failures in transmission towers before they affect operation."},"content":{"rendered":"

Paipe is a company focused on business and information technology solutions. It excels in service delivery and offers a portfolio of innovative solutions as its main deliverable, combining the needs and business requirements of its clients.<\/span><\/p>\n

It has a team of highly qualified collaborators and partner companies to design the best solutions. Thus, it develops business platform projects, mobile solutions, and other applications that utilize the most modern technologies on the market.<\/span><\/p>\n

Many clients seek out Paipe in search of solutions to existing problems. One of them presented a preliminary project idea involving data intelligence, artificial intelligence, and mathematical modeling.<\/span><\/p>\n

The initial contact with this company was made by Marcelo Dannus, CEO of Paipe, along with partners Rog\u00e9rio Nath, CEO of 4Show, and Professor Rodrigo Dalla Vecchia. The project scope was discussed and agreed upon in the initial stages, with a clear discussion of the needs, objectives, and expected results, mapping the entire process, opportunities, and the client's desires, with <\/span>focus on the main problem<\/span><\/a>.<\/span><\/p>\n

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The customer<\/span><\/h2>\n

This is a company with over 12 years of history that delivers M2M\/IoT connectivity solutions throughout Brazil. It helps its clients achieve maximum communication potential between devices, serving diverse applications across various sectors. Its purpose is to deliver the best Telecom experience for the Internet of Things (IoT) market.<\/span><\/p>\n

One of their solutions is to ensure connectivity in fleet vehicle tracking for large logistics companies, which monitor and track trips in real time.<\/span><\/p>\n

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The challenge<\/span><\/h2>\n

The challenge was to efficiently identify potential anomalies in transmission towers (antennas). When cargo vehicles go offline due to lack of mobile data, they become vulnerable to theft and loss. Therefore, keeping SIM cards operational is vital for delivery companies.<\/span><\/p>\n

Any problems that had previously occurred due to lack of connectivity were reported by the customers themselves. But with more than 280,000 antennas, this process became humanly impossible. The project's objective was precisely to reverse this logic: to start predicting possible failures in the company's networks, so that it could inform customers in advance about the measures to be taken. This was exactly what the customer was looking for when contacting Paipe.<\/span><\/p>\n

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The solution<\/span><\/h2>\n

Based on this, Paipe, in co-creation with the client, generated a feedback model from the company's internal team, allowing the sharing of information and knowledge between both parties. The project applies AI (artificial intelligence) with mathematical algorithms and machine learning concepts to the...<\/span> identification of anomalies in transmission towers<\/span><\/a> Signal to SIM cards, in real time.<\/span><\/p>\n

The AI algorithm, linked to a dashboard, spends all day diagnosing the client company's network, learning from each incident and providing advance warnings of potential failures.<\/span><\/p>\n

Minute-by-minute diagnosis<\/span><\/h3>\n

\u201c"Today, with the technology we've built, they know minute by minute what's going wrong, and they can already talk to customers, assist them, inform them that there's a problem, and that they're taking all possible actions to resolve it." \u2014 Rodrigo Dalla Vecchia.<\/span><\/p>\n

For the algorithm to be able to perform this quick reading, statistical techniques are used, along with machine learning and AI techniques, which help in making safe decisions.<\/span><\/p>\n

A lightweight algorithm, in seconds instead of minutes.<\/span><\/h3>\n

One of the biggest challenges of the project was creating a lightweight algorithm capable of delivering this data minute by minute. Currently, it takes 20 to 30 seconds to run, compared to around two minutes previously\u2014making the process much faster.<\/span><\/p>\n

What the dashboard shows<\/span><\/h3>\n

Among the information displayed on the platform's dashboard are:<\/span><\/p>\n