PREDICTIVE ANALYTICS IN THE MAINTENANCE AND RELIABILITY OF SATELLITE TELECOMMUNICATIONS INFRASTRUCTURE: A CONCEPTUAL REVIEW OF STRATEGIES AND TECHNOLOGICAL ADVANCEMENTS

Abstract

Predictive analytics is transforming the maintenance and reliability of satellite telecommunications infrastructure, offering proactive solutions to prevent downtime and enhance operational efficiency. This conceptual review explores key strategies and technological advancements driving the adoption of predictive analytics in this field. The integration of IoT devices and sensors enables real-time monitoring, providing valuable data on equipment performance and environmental conditions. Advanced algorithms, such as AI and ML, analyze this data to predict equipment failures and optimize maintenance schedules. These technologies improve the accuracy of predictive models, allowing companies to reduce downtime and improve overall infrastructure reliability. Challenges include data privacy and security concerns, as well as the integration of predictive analytics into existing maintenance processes. Companies must invest in specialized skills and expertise to implement predictive analytics successfully. Looking ahead, emerging technologies like real-time analytics and AI will continue to shape the future of predictive analytics in satellite telecommunications. Standardized practices, collaboration with industry partners, and a focus on data quality are essential for companies to harness the full potential of predictive analytics. In conclusion, predictive analytics is a game-changer for the maintenance and reliability of satellite telecommunications infrastructure. By adopting predictive analytics, companies can optimize maintenance processes, reduce downtime, and improve overall infrastructure reliability.
 Keywords: Predictive Analytics, Infrastructure, Telecommunications, Satellite, Reliability.