Reimagining Road Maintenance for Modern Times in the Age of Artificial Intelligence with Maintain-AI
Road infrastructure forms the backbone of any vibrant economy, ensuring connectivity and fostering economic growth. As the world grapples with rapidly changing climate patterns, urban expansion and escalating traffic volumes, roads and infrastructure face unprecedented stresses. Despite these challenges, the importance of highway maintenance and the maintenance and repair of roads cannot be overstated.
Traditional Pavement Management Systems (PMS), which have been reliable in the past, now require augmentation to meet the dynamic needs of today. Technologies like Maintain-AI, with their automated road assessment methodologies, promise an innovative, scalable and forward-thinking solution. This article delves into the prowess of Maintain-AI, highlighting its potential to pioneer next-gen, AI-powered asset road management that synergises with traditional PMS models.
Key article takeaways:
Modern Challenges, Modern Solutions: Traditional Pavement Management Systems (PMS) have been reliable in the past, but today's dynamic road infrastructure challenges necessitate innovative, AI-driven solutions like Maintain-AI to make a step change towards more proactive and efficient road maintenance strategies.
Operational Brilliance with AI: Maintain-AI's advanced AI and automation capabilities offer rapid and consistent pavement condition surveys, ensuring unbiased defect detection, enhanced safety and substantial cost savings for road agencies.
The Future of Road Maintenance: Beyond its current capabilities, Maintain-AI envisions a future where AI integrates with various data sources, offering predictive modelling, real-time dashboards and holistic, data-driven road asset management strategies.
Where could AI-based road inspections help you? Explore the potential of AI in road maintenance with our evaluation tool; a data-driven approach to understanding and optimising your infrastructure strategies. Try it here.
The Evolving Road Landscape and PMS
Overview of Existing PMS Systems
Emerging in the 1970s, Pavement Management Systems provided a structured framework for optimising budget allocation for road upkeep. These systems empowered network managers to prioritise road maintenance, analyse the balance between budgetary constraints and network health and devise both short-term and long-term action plans.
A few notable contributions of PMS include:
Transitioning from sporadic maintenance planning to structured budgeting and systematic programs.
Establishing standardised assessment methods for consistent road condition evaluations.
Cultivating performance prediction models and formulating treatment selection benchmarks.
Championing the philosophy of "Sustainability through Preservation".
However, while PMS introduced game-changing improvements, they are not without their drawbacks:
They often rely on limited manual inspection road data, leading to patchy network coverage.
The quality of inspection can vary with individual inspectors or individual contractors, leading to data inconsistencies.
Treatment recommendations do not account for real-time changes or near-current pavement health states.
Performance prediction models necessitate regular updates which is not always available from infrequently collected field data.
Given the dynamic nature of roadways infrastructure today, an enhanced strategy is a pressing need.
Challenges in Contemporary Maintenance
Adverse effects of climate change, such as flooding, wildfires and extreme weather conditions, have significant repercussions on road infrastructure, causing issues like erosion and heat-induced damage. Road safety research indicates the need for smarter, technology-driven solutions to predict and proactively address these impacts.
Big vehicles are also no longer the preserve of the few. The trending preference for bigger cars like SUVs and the subsequent increase in electric vehicles (EVs) is another sphere of concern. These vehicles exert more pressure on road surfaces, thereby degrading them at a faster pace. It is imperative to consider also that EVs are typically heavier than conventional cars due to the weight of their batteries. This escalated vehicular weight coupled with the increased volume of these vehicles results in more rapid wear and tear of a road’s surface, hence, necessitating more frequent maintenance and potentially, reconstruction.
Moreover, while the need for road maintenance is on the rise, agencies often face budgetary and manpower constraints. The essence of the challenge lies in achieving more with less, enhancing maintenance ROI, and minimising unplanned repairs. Relying solely on manual inspections is not feasible due to time, financial and safety implications. Furthermore, the limitations of sparse LiDAR-based inspection methods often leave knowledge gaps about the true health of roads, let alone the issues relating to the significant costs of their use.
This current landscape underscores the importance of blending human expertise with technological innovations to usher in an era of smart, automated and proactive road upkeep – which is possible with the opportunities afforded by automated road condition assessments.
The Merits of Embedding Maintain-AI into the PMS Framework
The Genesis of Maintain-AI
Maintain-AI was birthed with a vision to maximise the utility of every maintenance dollar spent through AI-powered road asset management. Drawing from years of experience in engineering and digital innovation, the founders identified several gaps:
Existing systems struggled with scalability, often failing to provide comprehensive network coverage.
The quality of objectivity of inspections varied widely, affecting data legitimacy.
Limited budgets often resulted in deferred maintenance, escalating lifecycle costs, reducing.
Although recently developed LiDAR-based systems are accurate, their high cost, complexity and infrequent use limit their potential to make timely data-driven decisions.
To address these issues, Maintain-AI harnessed advanced AI and computer vision methodologies to devise an automated pavement condition survey system. This system, characterised by its frequent, unbiased and actionable data, signals a shift from reactive to proactive road asset management strategies.
Recent advancements like LiDAR-based systems are undeniably accurate, but their considerable expense and limited use gives rise to infrequent data collection and hinders their transformative impact on decision-making processes. Real progress in improving road maintenance resides in consistently assessing a road's current condition state to apply the most cost-effective treatments at the most opportune times. This strategic approach will revolutionise future road maintenance, resulting in major performance improvements and more efficient use of funding. This is why Maintain-AI was conceived.
As per our company's ethos, Maintain-AI is committed to delivering a near fully automated pavement assessment process to ensure consistent, objective and scalable data collection and analysis. This aligns seamlessly with our mission of maximising the value of every dollar invested in road infrastructure and why good roads should cost less.
The Technological Backbone
At its core, Maintain-AI employs an AI-based automated road inspection system that utilises high-resolution imaging from mobile phones, mounted to a vehicle’s windscreen, to survey road conditions. Key features of the automated road survey system include:
An easy to use App that captures video data of the pavement surface, even at highway speeds.
Proprietary AI algorithms, rooted in deep learning and machine vision techniques, that detect pavement defects like cracks and potholes.
A cloud-based data provision pipeline for deriving actionable insights.
This revolutionary approach allows for rapid data collection at a fraction of the cost of manual or LiDAR based surveys, with a level of objectivity more consistent than human inspectors. The platform autonomously generates reports detailing defect types and condition scores and other insights from the captured data set.
By transforming raw pavement data into actionable insights, Maintain-AI equips road authorities with the tools to make more informed decisions. Some of the standout benefits include:
Covering significantly more area of manual inspections at reduced costs.
Conducting surveys as frequently as users request and need, enabling early detection of potential defects.
Achieving consistent surface defect detection observations, that continues to improve with further adoption and analysis.
Providing unbiased data that is not influenced by human error.
Offering customisable maintenance planning information that can support available budgets.
Complementing PMS with Maintain-AI
Despite the evident limitations of existing PMS systems, many road agencies are hesitant to discard them completely. This is where Maintain-AI excels – it is designed to enhance and complement existing frameworks, ensuring a seamless integration.
For instance, condition data from Maintain-AI can be incorporated into PMS performance prediction models, refining the recency of available road condition data. Moreover, Maintain-AI's detailed defect analytics can be utilised by treatment selection modules to provide more consistent and frequent maintenance recommendations.
In line with FAIR principles, Maintain-AI ensures that this critical condition data is Findable, Accessible, Interoperable and Reusable, thereby adding another layer of robustness to your existing PMS systems.
Furthermore, Maintain-AI's management dashboards are designed to integrate effortlessly with existing PMS platforms through API endpoints. This ensures a unified view of both manual and automated data collection, providing a comprehensive overview of network health. Thanks to its open architecture, processed data from Maintain-AI can be exported in desired formats, making it compatible with a range of analytical tools.
These API-based integrations enable road authorities to retain and leverage their investments in legacy PMS systems while simultaneously benefiting from the state-of-the-art features offered by Maintain-AI. By strategising and planning effectively, PMS and Maintain-AI can work in harmony, combining the strengths of both systems. The ultimate goal of Maintain-AI’s founders is to evolve with their partners through a collaborative approach, prioritising data-driven decisions to maximise maintenance ROI.
Value Proposition: Balancing ROI with Road Safety
Financial Efficiency with Maintain-AI
Road agencies invest significant sums in maintenance activities, ranging from pavement surface condition surveys to repairs and rehabilitation. By optimising these expenditures, Maintain-AI’s AI-based solution promises a compelling ROI in multiple areas:
Cost reduction in inspections: Automated surveys by Maintain-AI gather pavement data at a fraction of the cost of manual inspections.
Enhanced planning for maintenance: The system's rapid defect detection capability allows for the discovery of more timely minor repairs, negating the need for more extensive rehabilitations later on. Research indicates that preventive maintenance can be 10 times+ more cost-effective than replacing deteriorated pavements if defects can be identified early enough in the pavement degradation cycle.
Prioritising budget allocation: Comprehensive network-level analytics enables optimal budget distribution, ensuring maximum maintenance outcomes. Achieving additional lane-kilometre repairs, despite budget constraints ,will be possible after adopting an automatic road assessment philosophy.
While the exact ROI can vary, clients typically report considerable efficiency improvements across inspection, planning and rehabilitation phases. In an era of tight budgets, these savings can significantly boost the performance or road networks with available funds – improving safety, sustainability, user experience and user perceptions.
Eradication of discrepancies between different inspection teams.
Elimination of the need for lane closures, enhancing safety for workers and drivers.
Complete network coverage, removing the need for extrapolation from sampled data.
Higher frequency of surveys, ensuring proactive identification of defects.
Such automation translates to multiple operational advantages:
Refined planning based on comprehensive condition data.
Unbiased and objective defect detection that is not influenced by human subjectivity or oversight.
Enhanced road safety through proactive maintenance, preventing unexpected failures.
Ability to perform more frequent data collection at lower data costs
Efficient resource allocation, optimising labour, materials and equipment.
Policy decisions rooted in precise and current network-level analytics.
Overall cost effectiveness versus returns from improved road performance
Championing Safety and Sustainability
The repercussions of subpar road conditions extend beyond mere maintenance budgets. Road users incur billions annually in vehicle repairs and medical expenses due to accidents triggered by deteriorated pavements. Well-maintained roads can potentially reduce accidents related to poor roads by over 50% (sourced from various research articles).
Key areas where Maintain-AI enhances safety outcomes include:
Supporting a reduction in pavement-related accidents through proactive hazard detection.
Minimising accident risks for workers by eliminating the need for on-road inspections.
Swift incident response through quick identification of post-disaster issues.
Well-maintained roads also align with environmental and sustainability objectives:
Smoother pavements boost fuel efficiency and reduce emissions.
Preventing total rebuilds reduces material usage and minimises construction waste, greenhouse gas emissions and overall carbon footprints.
Enhancing resilience against extreme weather events.
The saying "Prevention is better than Cure" perfectly encapsulates the safety and sustainability benefits offered by Maintain-AI's road analyser solution.
Seamless Adoption and Integration
Despite its technological prowess, Maintain-AI's solutions are designed to translate intricate AI into straightforward, user-friendly applications. Road authorities can incorporate Maintain-AI's solution with minimal disruptions:
Comprehensive network-level surveys can establish baseline conditions and fine-tune existing PMS data.
Maintain-AI's onboarding approach supports seamless integration of APIs, data schemas and roles.
Ongoing support from the Maintain-AI customer success team ensures smooth adoption across organisations.
Customisation options cater to specific requirements for enterprise implementations.
Maintain-AI perceives successful adoption as a collaborative effort between its team and their partners. This synergistic approach ensures maximum value extraction with minimal disruptions to existing processes and systems.
According to the company's ethos, Maintain-AI provides flexible engagement models to ensure seamless integration with existing workflows. Our emphasis is on working collaboratively to better maximise the value of each dollar spent on asset management activities, reduce the lifecycle cost of owning our road networks and more importantly, improving user safety.
Maintain-AI stands at the cusp of transforming road asset management for the digital age. By infusing advanced AI into pavement inspections and maintenance planning, it can address and overcome many limitations inherent in traditional PMS. Its offerings in cost savings, safety, sustainability and overall performance position Maintain-AI as a cornerstone of next-gen road asset management frameworks.
As we look to the future, Maintain-AI is poised to build on its pioneering work to facilitate a more comprehensive, future-proof and data-driven approach to road infrastructure maintenance. With technological capabilities advancing at a rapid pace, the Maintain-AI team views the current landscape as just the beginning of a thrilling journey to engineer safer, smarter and more sustainable road infrastructure. Maintain-AI eagerly anticipates partnering closely with road agencies and owners globally to realise this vision and to promote good roads costing less.
Glossary of Terms:
Maintain-AI: Offers an advanced solution that uses computer vision and machine learning models to automate road surface inspections, enabling road asset professionals to make more informed and timely decisions.
Pavement Management Systems (PMS): Traditional systems used by road authorities to manage and maintain road assets based on manual or semi-manual inspections and assessments.
Computer Vision: A field of artificial intelligence (AI) that teaches machines to interpret and make decisions based on visual data, like images or videos.
Machine Learning: A subset of AI where computers learn from data without being explicitly programmed, making predictions or decisions without being specifically coded to perform the task.
Defect Detection: The process where the system identifies anomalies or damages on the road surface.
Distress Severity: The extent or degree of damage identified on the road.
Infrastructure Elements: Components of road infrastructure like signage, barriers, or markings that can be assessed using Maintain-AI.
Automated Pavement Surface Assessments: Modern AI technology-driven methods to inspect road conditions, as opposed to traditional manual surveys.
Pavement Preservation: The proactive approach in road maintenance where timely interventions are made to prolong the road’s lifespan.
Objective Inspections: Non-biased, data-driven evaluations performed by machines, ensuring consistency and repeatability.
Preventative Maintenance: Regular checks and minor fixes to prevent major damage to an asset in the future.
Road Network Images: Visual data captured from roads, processed by Maintain-AI for inspections.
Network Visualisation: A graphical and spatial representation of road conditions and other related data, aiding in better understanding and decision-making.
Data Collection Times: The frequency and duration required to gather sufficient data for analysis.
Subjectivity: Human biases that may influence decision-making or assessments.
ROI (Return on Investment): A measure of the profitability of an investment, indicating the benefits gained compared to the cost incurred.
Preservation Inspection: The regular assessment of road conditions with an aim to preserve and prolong its lifespan.
Assessment Strategies: Planned approaches to evaluate road conditions and determine necessary interventions.
Pavement Rehabilitation: The process of restoring damaged roads to their optimal condition.
Dashboards: User interfaces that visually represent data, analytics and other key metrics, aiding in easy interpretation and decision-making.
Frequently Asked Questions
What exactly is Maintain-AI and how does it fit into modern road asset management?
Maintain-AI is an innovative Company that leverages cutting-edge computer vision and machine learning models to automate road surface inspections. It detects surface defects and assesses the severity (including rating) of distresses, allowing road authorities to proactively manage their assets within shorter schedules. In essence, it offers a modern, data-driven approach to complement traditional pavement management systems (PMS).
How does Maintain-AI's approach differ from traditional PMS?
Traditional PMS often relies on manual inspections and assessments. Maintain-AI, on the other hand, employs automated road survey solutions, ensuring more frequent, objective and consistent inspections. This data-driven approach enables road professionals to make more informed and timely decisions, consistently monitoring road services and optimising road maintenance budgets.
How can Maintain-AI's approach to Automated Road Assessments enhance our existing PMS without entirely replacing it?
Maintain-AI is designed to augment, not replace. By providing objective and frequently collected high-quality GIS road data through innovative machine learning algorithms, it complements existing PMS, giving a fuller picture of road conditions and enabling proactive maintenance strategies.
What types of road defects can Maintain-AI detect?
Our intelligent technology is adept at identifying various defect types and distress severities across the road's life-cycle. Additionally, it can assess numerous associated infrastructure elements from the collected road network images, ensuring comprehensive coverage.
How does Maintain-AI support the philosophy that "Good Roads Should Cost Less"?
With our belief that prevention is better than cure, Maintain-AI emphasises consistent objective inspections and regular preventative maintenance. This approach not only maintains good roads but also ensures road maintenance budgets are maximised in value, making good roads cost-effective.
How do road authorities benefit from more frequent and consistent road inspections?
Frequent inspections allow for early detection and measurement of potential issues, enabling timely interventions. Consistent inspections to assess roads, powered by Maintain-AI’s machine learning solution, ensures objectivity, allowing road authorities to deploy resources more efficiently, with the goal of wanting to maximise the lifespan of roads.
How does Maintain-AI help in better communication of funding needs?
With objective data at hand, road authorities can more compellingly present their case for funding allocations. The visual dashboards and analytics provided by Maintain-AI give a clear picture of road conditions and maintenance requirements, facilitating better communication with stakeholders.
Can Maintain-AI integrate with our current road management software?
Maintain-AI is built with flexibility in mind. While specific integrations might require a tailored approach or customisation, our aim is to ensure that our solution can complement and enhance your existing road management systems with seamless access to consistent road data.
How does Maintain-AI contribute to sustainability in road maintenance?
By promoting the concept of pavement preservation and emphasising regular preventative maintenance, Maintain-AI ensures that good roads and motorways are maintained effectively. This proactive approach reduces excessive repair works, ultimately leading to lesser resource usage and environmental impact.
What kind of support and training does Maintain-AI offer to new adopters?
We are committed to ensuring a smooth transition for new adopters. We provide a dedicated support structure to assist you every step of the way. Our goal is to help road authorities and asset maintainers optimise their maintenance strategies with Maintain-AI seamlessly.
Let us know your thoughts?
Maintain-AI aspires to support Governments, other Road Asset owners and Industry professionals transform pavement and network assessments through AI-driven solutions. Founded on the principle that "Good Roads Should Cost Less", we harness the power of computer vision and machine learning to automate road surface inspections. Our state-of-the-art tools detect road defects and assess related infrastructure, enabling professionals to make data-driven decisions. By advocating for the optimal use of maintenance budgets, we emphasise that well-maintained roads are more cost-effective across a road's complete asset lifecycle. Our commitment is to support regular, objective network inspections, ensuring that every maintenance dollar is maximised. With Maintain-AI, infrastructure asset management is not only efficient but also offers a clear return on investment through maintenance savings. Join us in our mission to make roads better, safer, more sustainable and more cost-effective. All road users deserve it.