Increased Data Analytics Capabilities Revolutionized The Tower Industry

Data analytics capabilities have absolutely transformed the tower industry. Here's what to know.

5 Min Read
Shutterstock Licensed Photo - By SFIO CRACHO | stock photo ID: 447406060

At one point, inspection procedures in the tower industry were somewhat negligent at best. Early personal cellular services didn’t have to answer to regulatory organizations, which gave the entire industry a wild west feel. Managers were able to promote whatever techniques they wanted, and most technicians were more concerned about cost cutting than anything else. Very little data was collected in regards to whether or not different procedures actually worked.

Regulatory agencies have passed a number of landmark policies that have drastically changed how this work is done. At the same time, the 5G migration is increasing the complexity of site inspection. A majority of new tower construction projects are actually in populated areas, which has increased how much individual companies are promoting safety issues.

That’s created something of a rush where almost every major player in the industry is looking at adapting data analytics software to test the quality of their tower inspection workflows.

Data Analytics Software for the PCS Industry

A drastic increase in the need to inspect new sites has also caused an uptick in the amount of data that has to be collected and processed on a daily basis. Modern tower inspection software packages are designed to perform an in-depth survey of data collected from tower sites to help ensure safety and increase profitability.

Once a company has collected enough raw information about its operations, it should be able to predict when the possibility of a problem might arise. These software packages monitor issues until they’re able to spot the conditions that make a problem likely to happen. As a result, they’ve become especially popular with smaller tower inspection firms that don’t have large crews to dedicate to specific areas.

Maintenance costs will continue to spiral for anyone who installs a cellular tower unless they’ve implemented this kind of system. That fact alone has helped to ensure that countless firms are starting to adopt predictive analytics so they don’t have to suffer through the indignity of sudden downtime.

Predicting the Chances of a Network Outage

Considering the costs associated with experiencing frequent network outages, some companies are turning to big data processing systems in order to calculate the chances of these happening. At first, firms were only concerned with doing so in order to assign crews preemptively to certain areas as a sort of preventative medicine.

More recently, tower operators have rededicated themselves to figuring out more about what conditions make it likely that a tower goes down. Once they’re aware of this possibility, managers are in a much better position to reduce the risk of it happening.

Data collected from individual sites has to be structured in some way before it can be used to predict the likelihood of certain events, however. It’s not currently possible to use raw information to make predictions.

Quite a few coders have recommended predicative blockchain data paradigms, which sort events based on the transactions that are recorded whenever something happens. Transactional databases can’t be altered once the changes have been written to a virtual disk image, which almost completely eliminates the risk of tampering with them.

Some experts feel that this can help to dramatically cut field time down to around 40 minutes at the most while also slashing the number of people that are required for each inspection. However, it’s not the only technology that data processing experts are using to predict the chances of a cellular tower failure.

Figuring Out When Disaster Might Strike

Self-balancing trees are being promoted as a potential solution by many in the computer science community. While storing data in such a traditional format might not be the flashiest way of doing things, it’s reaping big benefits for some larger organizations. These trees sort tower failures and uptime statistics into a concrete structure that includes at least two child nodes for each event. A computer program would simply need to trace the nodes to find out the probability of an event repeating itself.

Regardless of which technology specialists elect to go with, it looks like a strong focus on predictive analytics will improve the quality of cellular communications and reduce the risk of costly tower infrastructure accidents.

Share This Article
Exit mobile version