Predictive maintenance

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Providers need to optimize energy consumption – not only because of price, but also because of the transition to carbon neutrality for environmental reasons.

AI can dynamically regulate the energy consumption of base stations. Neural networks analyze traffic patterns and predict times of low demand, then temporarily turn off some network components without affecting service quality.



Using sensors, algorithms can analyze vast amounts venezuela telegram of data about network equipment to identify anomalies (such as temperature, vibration, and signal quality). This allows failures to be predicted before a machine fails and action to be taken—scheduling a technician or replacing the equipment.

Another option is to train AI models on historical data so that they can predict which components are likely to break based on experience. This data can be used to create a maintenance schedule.

AI has the potential to reduce downtime by approximately 5-15%, according to IBM estimates, and reduce repair costs.

On the topic. Experts named Russia one of the most favorable countries for the development of artificial intelligence



How AI is being used to monitor fires and find criminals
I will give two examples of AI implementation in mobile communications from my own practice. The solutions were implemented as demonstration stands for European operators. Thanks to them, it was possible to save network resources and provide a high level of service when necessary.

Example #1: Environmental monitoring. National parks and reserves usually have cameras installed to help spot fires and other emergencies in time. To save resources, they operate in low-bandwidth mode. This means that the image they transmit is of poor quality. When detecting smoke, AI can automatically increase the bandwidth and transmit clear footage. This will allow decisions to be made based on complete information.