Sandeep Gill’s Post

With the rapid evolution of artificial intelligence (AI), network automation is becoming a game-changer for microwave networks, helping to reduce operational expenses (opex) in various ways. A notable example is the Spanish service provider Lineox, which has successfully reduced site visits by 40% through the use of automatic scripts. AI-driven network automation offers multiple benefits: 🔋 Reduced Power Consumption: Automated radio deep sleep scheduling can lower energy costs. 🛠️ Efficient Troubleshooting: Precise root cause analysis can address tower sway, antenna misalignment, and signal degradation swiftly. 🛡️ Preventive Maintenance: Early warnings for hardware degradation and network traffic forecasts help prevent costly emergencies. Lineox's achievements highlight the potential of AI in network management. By leveraging automated alarm filtering and performance management data, they prioritized issues effectively, reducing unnecessary site visits and cutting operational costs. The key to success lies in relevant network data—topology data for software upgrades, frequent signal quality measurements, and historical data for trend analysis. When combined with AI-based training and robust algorithms, accuracy in predictions and event classifications can exceed 99%. Lineox's journey showcases the transformative impact of AI in network management. By continuing to harness AI, service providers can expect optimized performance, higher energy efficiency, and a superior end-user experience. How do you see AI transforming network operations? Share your insights in the comments below. #AI #NetworkAutomation #MicrowaveNetworks #Innovation #AIinTelecom

With the rapid evolution of artificial intelligence (AI), network automation is becoming a game-changer for microwave networks, helping to reduce operational expenses (opex) in various ways. A notable example is the Spanish service provider Lineox, which has successfully reduced site visits by 40% through the use of automatic scripts. AI-driven network automation offers multiple benefits: 🔋 Reduced Power Consumption: Automated radio deep sleep scheduling can lower energy costs. 🛠️ Efficient Troubleshooting: Precise root cause analysis can address tower sway, antenna misalignment, and signal degradation swiftly. 🛡️ Preventive Maintenance: Early warnings for hardware degradation and network traffic forecasts help prevent costly emergencies. Lineox's achievements highlight the potential of AI in network management. By leveraging automated alarm filtering and performance management data, they prioritized issues effectively, reducing unnecessary site visits and cutting operational costs. The key to success lies in relevant network data—topology data for software upgrades, frequent signal quality measurements, and historical data for trend analysis. When combined with AI-based training and robust algorithms, accuracy in predictions and event classifications can exceed 99%. Lineox's journey showcases the transformative impact of AI in network management. By continuing to harness AI, service providers can expect optimized performance, higher energy efficiency, and a superior end-user experience. How do you see AI transforming network operations? Share your insights in the comments below. #AI #NetworkAutomation #MicrowaveNetworks #Innovation #AIinTelecom

Introducing Cognizant Neuro® Edge: Revolutionizing AI Deployment at the Edge Cognizant Neuro Edge is a powerful example of Cognizant's leadership in developing a new approach to layering of on-board computing and processing with cloud services, paving the way for businesses to unlock a range of generative AI-driven benefits around operational efficiency, cost and risk reduction. Healthcare: Assisting doctors in their real-time decision-making by drawing on diagnostic sensors; MedTech: Enabling real-time, on device adjustment options and recommendations based on patient data; Energy: Optimizing operations in power generation plants; optimizing response to weather events; Logistics: Streamlining fleet performance and reducing downtime through in-vehicle data processing; Telecommunications: Enhancing network security, resiliency and automation, leading to lower operating costs; Manufacturing: Predicting equipment failures to help optimize uptime and operating costs; Retail: Enabling intelligent video analysis for real real-time theft prevention and in-store traffic pattern monitoring to enhance customer service; Automotive: Transforming driver and passenger experience by enabling real-time, context-aware and private recommendations via cloud connection. Learn more about Cognizant Neuro Edge: https://cogniz.at/45PHm4g

With the rapid evolution of artificial intelligence (AI), network automation is becoming a game-changer for microwave networks, helping to reduce operational expenses (opex) in various ways. A notable example is the Spanish service provider Lineox, which has successfully reduced site visits by 40% through the use of automatic scripts. AI-driven network automation offers multiple benefits: 🔋 Reduced Power Consumption: Automated radio deep sleep scheduling can lower energy costs. 🛠️ Efficient Troubleshooting: Precise root cause analysis can address tower sway, antenna misalignment, and signal degradation swiftly. 🛡️ Preventive Maintenance: Early warnings for hardware degradation and network traffic forecasts help prevent costly emergencies. Lineox's achievements highlight the potential of AI in network management. By leveraging automated alarm filtering and performance management data, they prioritized issues effectively, reducing unnecessary site visits and cutting operational costs. The key to success lies in relevant network data—topology data for software upgrades, frequent signal quality measurements, and historical data for trend analysis. When combined with AI-based training and robust algorithms, accuracy in predictions and event classifications can exceed 99%. Lineox's journey showcases the transformative impact of AI in network management. By continuing to harness AI, service providers can expect optimized performance, higher energy efficiency, and a superior end-user experience. How do you see AI transforming network operations? Share your insights in the comments below. #AI #NetworkAutomation #MicrowaveNetworks #Innovation #AIinTelecom

With the rapid evolution of artificial intelligence (AI), network automation is becoming a game-changer for microwave networks, helping to reduce operational expenses (opex) in various ways. A notable example is the Spanish service provider Lineox, which has successfully reduced site visits by 40% through the use of automatic scripts. AI-driven network automation offers multiple benefits: 🔋 Reduced Power Consumption: Automated radio deep sleep scheduling can lower energy costs. 🛠️ Efficient Troubleshooting: Precise root cause analysis can address tower sway, antenna misalignment, and signal degradation swiftly. 🛡️ Preventive Maintenance: Early warnings for hardware degradation and network traffic forecasts help prevent costly emergencies. Lineox's achievements highlight the potential of AI in network management. By leveraging automated alarm filtering and performance management data, they prioritized issues effectively, reducing unnecessary site visits and cutting operational costs. The key to success lies in relevant network data—topology data for software upgrades, frequent signal quality measurements, and historical data for trend analysis. When combined with AI-based training and robust algorithms, accuracy in predictions and event classifications can exceed 99%. Lineox's journey showcases the transformative impact of AI in network management. By continuing to harness AI, service providers can expect optimized performance, higher energy efficiency, and a superior end-user experience. How do you see AI transforming network operations? Share your insights in the comments below. #AI #NetworkAutomation #MicrowaveNetworks #Innovation #AIinTelecom

The AI Revolution and 5G ... Integrating artificial intelligence (AI) into daily life is reshaping mobile networks, particularly radio access networks (RAN), to accommodate a surge in uplink traffic. This transformation is crucial as AI applications generate significant data, necessitating robust uplink connections. Companies like SoftBank are already adapting their network architectures in collaboration with Nokia to prepare for this increase in data traffic. AI-generated traffic is characterized by its bursty nature, where short, intense data spikes occur rather than a steady flow. Applications like AI photo editing can lead to uplink usage spikes of tens of Mbps, while voice interactions require consistent uplink speeds of 1-3 Mbps. These demands highlight the need for networks to evolve beyond traditional downlink-focused optimizations. Mobile network operators are urged to conduct traffic modeling, invest in infrastructure upgrades, and collaborate with AI developers to optimize applications for network efficiency. As AI applications become more prevalent, traditional strategies must shift to accommodate increased uplink demands. The AI revolution already impacts mobile networks, necessitating adaptations to handle unique traffic demands. Embracing these changes will enable operators to leverage new monetization opportunities and improve service quality for users engaging with AI-enhanced applications. #5g #genai #ai

🚀 **AI in 5G Deployment: Revolutionizing Network Planning and Optimization** 🚀 As 5G technology continues to roll out globally, the role of AI in enhancing its deployment has become increasingly vital. Here’s how AI is transforming network planning and optimization: 🔍 **Predictive Analysis**: AI algorithms analyze vast datasets to predict network traffic patterns, helping telecom operators anticipate demand and allocate resources efficiently. 📈 **Dynamic Resource Management**: AI-driven systems can dynamically adjust network parameters in real-time, ensuring optimal performance and minimizing latency. 🛠️ **Automated Troubleshooting**: By leveraging machine learning, AI can detect and diagnose network issues more quickly than traditional methods, reducing downtime and enhancing user experience. 🌐 **Enhanced Coverage**: AI helps in designing network layouts that maximize coverage and capacity, especially in densely populated urban areas. 🏗️ **Cost Efficiency**: Streamlined operations and reduced manual intervention lead to significant cost savings, making 5G deployment more economically viable. The integration of AI in 5G isn’t just a technological advancement; it’s a game-changer for industries and consumers alike. As we move forward, expect AI to play an even more critical role in making 5G networks smarter, faster, and more reliable. #AI #5G #NetworkOptimization #Telecommunications #Innovation What are your thoughts on AI-driven 5G deployment? Share your insights in the comments below! 👇

With the rapid evolution of artificial intelligence (AI), network automation is becoming a game-changer for microwave networks, helping to reduce operational expenses (opex) in various ways. A notable example is the Spanish service provider Lineox, which has successfully reduced site visits by 40% through the use of automatic scripts. AI-driven network automation offers multiple benefits: 🔋 Reduced Power Consumption: Automated radio deep sleep scheduling can lower energy costs. 🛠️ Efficient Troubleshooting: Precise root cause analysis can address tower sway, antenna misalignment, and signal degradation swiftly. 🛡️ Preventive Maintenance: Early warnings for hardware degradation and network traffic forecasts help prevent costly emergencies. Lineox's achievements highlight the potential of AI in network management. By leveraging automated alarm filtering and performance management data, they prioritized issues effectively, reducing unnecessary site visits and cutting operational costs. The key to success lies in relevant network data—topology data for software upgrades, frequent signal quality measurements, and historical data for trend analysis. When combined with AI-based training and robust algorithms, accuracy in predictions and event classifications can exceed 99%. Lineox's journey showcases the transformative impact of AI in network management. By continuing to harness AI, service providers can expect optimized performance, higher energy efficiency, and a superior end-user experience. How do you see AI transforming network operations? Share your insights in the comments below. #AI #NetworkAutomation #MicrowaveNetworks #Innovation #AIinTelecom

With the rapid evolution of artificial intelligence (AI), network automation is becoming a game-changer for microwave networks, helping to reduce operational expenses (opex) in various ways. A notable example is the Spanish service provider Lineox, which has successfully reduced site visits by 40% through the use of automatic scripts. AI-driven network automation offers multiple benefits: 🔋 Reduced Power Consumption: Automated radio deep sleep scheduling can lower energy costs. 🛠️ Efficient Troubleshooting: Precise root cause analysis can address tower sway, antenna misalignment, and signal degradation swiftly. 🛡️ Preventive Maintenance: Early warnings for hardware degradation and network traffic forecasts help prevent costly emergencies. Lineox's achievements highlight the potential of AI in network management. By leveraging automated alarm filtering and performance management data, they prioritized issues effectively, reducing unnecessary site visits and cutting operational costs. The key to success lies in relevant network data—topology data for software upgrades, frequent signal quality measurements, and historical data for trend analysis. When combined with AI-based training and robust algorithms, accuracy in predictions and event classifications can exceed 99%. Lineox's journey showcases the transformative impact of AI in network management. By continuing to harness AI, service providers can expect optimized performance, higher energy efficiency, and a superior end-user experience. How do you see AI transforming network operations? Share your insights in the comments below. #AI #NetworkAutomation #MicrowaveNetworks #Innovation #AIinTelecom

With the rapid evolution of artificial intelligence (AI), network automation is becoming a game-changer for microwave networks, helping to reduce operational expenses (opex) in various ways. A notable example is the Spanish service provider Lineox, which has successfully reduced site visits by 40% through the use of automatic scripts. AI-driven network automation offers multiple benefits: 🔋 Reduced Power Consumption: Automated radio deep sleep scheduling can lower energy costs. 🛠️ Efficient Troubleshooting: Precise root cause analysis can address tower sway, antenna misalignment, and signal degradation swiftly. 🛡️ Preventive Maintenance: Early warnings for hardware degradation and network traffic forecasts help prevent costly emergencies. Lineox's achievements highlight the potential of AI in network management. By leveraging automated alarm filtering and performance management data, they prioritized issues effectively, reducing unnecessary site visits and cutting operational costs. The key to success lies in relevant network data—topology data for software upgrades, frequent signal quality measurements, and historical data for trend analysis. When combined with AI-based training and robust algorithms, accuracy in predictions and event classifications can exceed 99%. Lineox's journey showcases the transformative impact of AI in network management. By continuing to harness AI, service providers can expect optimized performance, higher energy efficiency, and a superior end-user experience. How do you see AI transforming network operations? Share your insights in the comments below. #AI #NetworkAutomation #MicrowaveNetworks #Innovation #AIinTelecom