For a Wireless Service Provider, the energy consumption at the cell towers is a significant part of the Operation cost (OPEX).
CEMtics helped a Tier 1 Wireless Service Provider to Quantify and Optimize the energy costs.
Cemtics team used the network and with external data like weather and temperature data to predict the energy consumption on cell towers using advanced machine learning.
This was used not only to audit the data from the utilities but also to flag inefficient hardware (for replacement), and recommend network parameter changes in non-peak usage hours to reduce energy consumption.
For an operator a typical Customer Care life cycle involves heavy dependence on manual tasks, multiple stakeholders and processes to tackle a Customer Experience issue.
Lack of details of the issue faced by a customer also impacts Care’s understanding of the actual problem statement.
This predicament along with the complex process in place causes Operator significant Lead Times. Money & Mobilization of resources without any clear solution for the Customer.
CEMtics helped a tier 1 operator devise a mechanism to automate the Customer Care analytics for customer issue troubleshooting. CEMtics used data points from Customer Network Experience data , Calling pattern records, Location info to carry out Clustering , Detect anomalies and run correlation in the – Time, Network , Geo spatial & Influencer – domains. This enabled the operator to gain insights into customer’s - Live Work Play locations , Classify and categorize customer’s issue , Auto identify nodes(s) causing issue & ascertain impact on customer’s influencer network.
Created strategy and execution plan for an E2E Network Planning tool for a Green field LTE / VoLTE network with more than 100,000 multi carrier sites.
● Evaluated capacity bottlenecks for every network element
● Created KPI’s to measure the bottlenecks
Data Analytics and Modelling of
● Modeling Traffic Growth including seasonality
● Geographic traffic distribution using social media traffic
● Modeling of Customer Data & Voice usage patterns.
Software Development and Automation of
● Configuration management data collection from Network Elements
● Performance Data and aggregation
● Network Utilization and customer usage reports
Worked with Tier 1 operator to create a holistic view of the network merging the RAN network topology with the Backhaul / IP network.
● Identified internal data sources and the methodology to merge RAN and IP network data.
● Created a working prototype by using state of the art graph database and visualization tools.
● The proposed solution was 5x time more efficient w.r.t. response time compared to existing "old school" solutions
● Built the methodology and a prototype to identify sites in a ring, ring capacity and impact due to failures.