Has it ever occurred to you that a corner of your home which you never thought would never have any tangible issues, shows up as a miscreant for regular maintenance? Have you ever thought “Oh I wish I had known of this problem with my gadget or my building or my infrastructure beforehand so that I could give timely attention to it and get it repaired?

Well, this must have certainly happened to you at least once in your lifetime. We all go through this. Everything seems to be working perfectly in tandem for us until one day some machine breaks down or some part of our house cracks up because of the prolonged effect of inclement forces on them. The case is no different for industries too. Even during the production floors, technicians keep facing hassles in repairing machines that have undergone serious technical breakdown. And no wonder, such issues are preventable if there is a continuous check being done on the machines, or any other kind of infrastructure as a matter of fact. This is what we call “predictive maintenance” in the intelligent industry language. Predictive Analytics on machines can help identify issues very well in advance and can help to notify the technicians and the other factory operators regarding the symptoms of malfunction in a piece of infrastructure. This can go a long way in alerting the maintenance teams and getting them to swing into action to fix the technical issues before the infrastructure faces a massive failure, thereby disrupting the entire value chain.

Now a person knowledgeable about the emerging technology trends will simply say that predictive maintenance is already a part of smart factory operations. What’s so new about this concept? Well yes, I know that predictive maintenance is already growing into a veteran in the family of intelligent industrial technologies. But what if I told you that there is a new member that is going to take predictive analytics and predictive maintenance to an altogether new level? What if I told you that drones would be the new navigators of some of the most amazing use cases of predictive maintenance? Surprised? Well, don’t be! Because drones are the next big thing in the intelligent industry paradigm. And soon we may have a day when drones would be acting as the doctors for the first level of prognostic diagnosis of infrastructure facilities in a multitude of industries.

Drones in Factory Maintenance

Factory buildings can wear out over the course of time and can start getting damaged under the influence of changing climatic patterns. Moreover, the installations on the factory buildings may also fall a prey to the vagaries of nature and can face damages which may skip the notice of the factory operators. In such cases, predictive maintenance using IoT sensors may not help much, since the sensors may not be able to give precise information on the magnitude of damage. This is where the factory owners need to closely check the equipment to understand the scale of damage. And in case a human eye skips noticing them, then such issues can swell in magnitude over the passage of time.

This is where factory operators need a system to keep a regular check on any damage or malfunction occurring in any corner of the factory. And this is exactly where drones emerge as a viable option. With their ability to maneuver effortlessly in nooks unreachable for humans and their capability in doing a thorough aerial surveillance, the drones of tomorrow will seamlessly combine their flight capabilities with image analytics to decode any technical or structural issue at any site in the factory premises. Granular level of image analytics will help to find any deviation from the benchmark parameters in the image. For example, if a building shows signs of damage due to weather, or any facility shows signs of growing misalignment with the expected orientation, which can trigger an alert. Certainly, the drone will be capturing images and edge analytics algorithms will run through them, in order to bring analytics closer to the drone. There is not going to be any wastage of time in storing the images on a central cloud system and then getting the output from it, before taking any decision. The decisions will be taken right at the drone level and the next course of action will be decided on the spot. In case the drone’s image analytics identifies that there is a particular kind of anomaly in the observations, the surveillance drone will decide to approach the site of damage for a closer inspection. In case any damage is confirmed, the autonomous predictive maintenance engines will be pumped into action. The factory operators will be notified and will be requested for confirmation on swinging the maintenance procedures into action. Once given a green signal from the factory operators, the repairing robots will get into action and will follow the automated procedures for regular maintenance activity. In case the work is identified to be beyond the capability of the robots and process automation, a particular set of factory technicians will be assigned to this job based on their availability and competencies. The drone will add this activity to its daily schedule and will monitor the daily progress made on the maintenance activity. Predictive maintenance driven by drones for surveillance will be the new norm for the smart factories of tomorrow.

Drones in Tower Maintenance

High-rising towers in the electricity grids and the telecom industry are sometimes difficult to maintain. Even if the IoT sensors connected to the machines communicate any malfunction of the installed equipment, a technician will need to take a closer look at the machines and make adequate preparations for fixing the technical issue. However, given the height of the towers, it can become extremely cumbersome to climb the tower and then identify the issue. It is certainly a better option for something to provide that clear picture to the technicians before they climb the tower, so that they are better prepared for the technical issue they are going to solve.

Enter the surveillance drones. Instead of technicians going atop a telecom tower or an electricity grid tower, a drone can be sent to fly high in the air and access the installed equipment at the heights of the towers. The drones can easily capture and stream the videos to the on-ground tower operators, who can have a 360-degree view of the tower and can then study the footage to understand where the technical issue lies. Or even better, the image analytics and video analytics engines can study the captured recordings and run their algorithms to identify where the issue lies. This will be supplemented by the IoT sensor data that will help to pinpoint the actual technical matter that needs attention. As a result, the technicians will be in a better position to take the right decisions for the correctly identified problems.

This reduces the operational wastages of waiting and over-processing. Aided by the drones, the technicians won’t have to process much of information as the IoT sensor data and the drone’s analytics will identify what steps are to be taken by the technician and how the matters are to be resolved with minimum investment of time. As a result, the maintenance work for the towers will get completed quicker and will lead to massive savings for the telecom and energy & utilities sector.

Drones in Railways

When was the last time you thought about drones helping in the railways sector? Well, if you never did, today you will. Keeping a track of the railways infrastructure facilities can be quite cumbersome, for no one clearly may know how to identify the potential issues. It may be the case that at some unmonitored place, the railway tracks may have shifted. Or at some places there is disruption over the railways tracks. Or even worse, some location on the course of the railway tracks may be inundated under water or covered under snow. All these situations can be extremely dangerous for the trains that ply over the tracks. And keeping an eye over the entire railway line is certainly a huge investment of human resource and money. What if surveillance drones could perform the task of a third eye? Sounds interesting? Let’s explore it further.

Drones can capture the aerial footage of the railway tracks and the image analytics algorithms can then work on the footage to identify any potential disruption along the railway lines. In case of any disruptions identified, the railway maintenance operators can be notified and alerted regarding the issue, so that the trains scheduled to run on that track are halted in time. Next, the image analytics can also help identify the exact issue with the infrastructure facilities and can assign the task to the right team autonomously. Based on the availability of the technicians, the right team can be assembled and can be notified about the location to report at. It may not take you long to imagine the way aerial surveillance through drone can actually accelerate the repair and maintenance activities for the railways sector. The implications will be constructive and massive.

Drones for forest surveillance

Yes, you read it correct! Dense forests are some of the most inaccessible places on the planet and any road passing through them needs to be always in a functional state. Or else, the entire passage meandering through a forest may get blocked because of some disruption. Felling of a tree, or presence of a living/dead animal on the road can indeed block the passage. And by the time authorities get to know about the issue, there would already be a long traffic jam impeding the maintenance process.

This is where drones can be instrumental in driving autonomous surveillance of the forest areas, where authorities cannot be always present. Quick identification and classification of the infrastructural issues can help to move the right maintenance teams quickly into action and get the things moving to restore the infrastructure in the forests. Drones can enable aerial surveillance which lead to quicker resolution of issues, for the benefit of the public.

In a nutshell

Drones are the next big thing in the world of predictive maintenance of infrastructure facilities. They are already doing awesome in field surveillance and farm monitoring. They are also lending a helping wing in the area of natural disaster management by surveying the areas under floods or avalanche. However, new use cases will also emerge for drones, making them much more relevant and integral to the process of predictive maintenance and prognostics. Don’t be surprised if tomorrow a drone is given a large share of the credit for keeping our public infrastructure safe and sound, for that day is arriving sooner than you can imagine.