Managing road infrastructure is an integral role that the government carries out. A portion of the hard-working taxpayer’s money goes into maintaining such infrastructure. Since the failure to maintain road infrastructures could lead to public inconvenience or injure citizens at its worst, road managers hold the pressure to monitor, maintain and prevent roads from being damaged. It is hard for humans to monitor road assets daily and detect any damages in their initial stages. Hence, most often, considering that it also takes a long time for a team of experts to collect data, by the time the damage is detected, it requires an enormous amount of money to be incurred for repairs.
When it comes to asset management, road managers focus on two aspects. This includes corrective and predictive maintenance. Corrective maintenance assesses the correcting infrastructure damages and failure, whereas the latter concentrates exclusively on reducing the probability of failures. This article will explain how smart predictive technologies help road managers.
What is Predictive Technology?
Predictive technology refers to the infusion of data science and predictive analytics whereby patterns are forecasted based on processing current and historical data. Initially, predictive technology was used to study socioeconomic activities, the stock exchange, the weather, and various other needs. Subsequently, they are now used by utility asset managers and other industries to maintain assets that are too expensive to repair. Not only is predictive technology meant to help companies reduce their overall finances, but it also helps reduce asset and infrastructure failures, degradation and suboptimal performances in a single effort.
Predictive technologies are broadly branded as those that implement predictive analytics. It is a tool which constantly analyses patterns and can detect fraud, and schedule replacements, adjustments, renewals, significant overhauls, replacements and inspections. Once a risk is detected and notified to the manager, the company can choose to carry out repairs during the system downtime or while the system is in operation. The most significant advantage is that companies can budget and schedule maintenance earlier and provide complete control to the manager to prevent random breakages. The main types of predictive maintenance include:
Condition Based Monitoring
In condition-based monitoring, predictive analytical tools are utilised to assess the physical conditions of the asset. A measurable parameter is used to consider the degradation of the asset and the potential for it to fail. This data is received by condition monitoring techniques, including direct and indirect measurements. Sensor technologies, in this regard, play a pivotal role in condition-based monitoring. As the name suggests, it consistently monitors the asset’s condition and notifies the manager of any changes that occur, no matter how minute. This is an ideal way to detect the root cause of dangerous road assets.
This refers to a form of predictive maintenance in which action is carried out in a planned order. In other words, the organisation would make a timeline as a predetermined rule, listing out the steps that will be taken to repair or carry out maintenance of equipment. Hence, a road manager could agree to carry out repairs on a set period or by measuring the operation of a machine. Thus, for instance, repairs will automatically be carried out once every six months or could be based on the frequency of heavier vehicles that go on the road and could potentially cause damage to the asset. The central factor used to determine which predetermined rule will be used is decided during the design and construction stage of the road. National and international regulatory regimes guide road managers to make the right decisions.
Five Smart Road Technologies Powered By Predictive Analytics
Many technologies are adopted to collect big data as they are required to help asset managers successfully predict asset failures or their deterioration. Here are five such smart technologies adopted by road infrastructure managers today:
Artificial Intelligence (AI) and Machine Learning (ML)
AI and ML are at the very heart of all intelligent technologies today. The power unlocked by these two technologies carries out the process of adapting, self-learning and self-predicting. Road asset managers utilise all the technologies to collect big data into one central platform. Once integrated, AI and ML work in real time to process, store and assess all the compiled information. Therefore, it can use information in the system and historical data that had led to past breakages to make a data-driven decision to warn the manager of a future risk that the road assets may suffer with a high level of accuracy.
Industrial Internet of Things (IIoT)
IIoT mainly incorporates a range of sensors for its functions. Hence, road managers invest in sensors fixed to the ground level in various parts of the city. This is an easy method to keep track of an entire road network. It consistently monitors the infrastructure and can detect atmospheric pressures and the energy released due to ill maintenance. Hence, sensors can provide data on a range of things, helping data scientists understand the factors that have led to the deterioration of road infrastructures. In other words, IIoT surges data to dynamic predictive models to give insights into impending parameters like road degradation, performance, risks, and costs simultaneously.
Geographic Information System (GIS) Technology
GIS technology provides city-wide visualisation capabilities. It helps utility managers to comprehensively and automatically map transportation asset networks based on their conditions. It highlights which assets require the most attention and can illustrate transportation network pavement and surface indexes. It can also enable fast road condition diagnosis and presents all the information managers need to make informed decisions under one smart screen. It is an integral type of technology used to improve highway traffic safety and manage and maintain all forms of transportation infrastructures, including bridges and culverts. The GIS layers are most insightful when they are powered by predictive analytics, allowing road managers to use an interactive map to pre-assume the forthcoming road asset management concerns.
CCTV And Laser
CCTV and laser technologies are regarded as inspection robot fleets that detect structural transportation requirements. It does this in a matter of minutes, thereby detecting a range of infrastructure damages. This includes monitoring any formation of road cracks such as longitudinal, alligator, transverse, wheel track, etc. It can also detect potholes even in their smallest size, thereby finding bleeding, edge or friction surfaces at its initial stages. The visual data gathered by IIoT-driven CCTV will automatically be stored as cloud back-ups. This information is vital for data analysts to run predictive algorithms and prioritise the critical infrastructure of the road systems and tailor condition-based maintenance programs.
Interferometric Synthetic Aperture Radar (InSAR)
InSAR is a form of satellite-based technology that can detect long-term criticality and monitor the deterioration of transportation infrastructure in large areas spanning as far as 120,000 KM. It uses advanced remote signalling to monitor road infrastructures by considering variables such as community impacts, road usage, and demographic data. It warns managers of slope instabilities and can take weather patterns to predict natural disasters. Hence, where the area is prone to landslides, managers can take measures to protect or strengthen road infrastructure to ensure menial damage. Sinkholes, floods, and other detrimental threats can also be detected using satellite technologies.
The Smarter Predictive Technologies Incorporated The Safer the Road Infrastructure
Smart predictive technologies work together to provide more accurate forecasts for road asset managers. In other words, although each of the technologies does have its role in collecting data and monitoring road assets, they must be integrated into one platform to assess the overall impact it could have on your operations. Find a software vendor like Tigernix, which can provide a range of advanced smart technologies to help prevent assets from being dangerous to the public.