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Historically, the design and planning phases of a construction project were reliant on manual survey methods, presenting static blueprints to the person or team responsible for planning the project. As a result, manual processes could create inefficiencies through communication gaps and unanticipated risks. Today, as a result of the combination of Artificial Intelligence (AI) technology and the availability of Geo-spatial tools, the Construction Industry is now experiencing a significant shift in its paradigm. The introduction of Geo-spatial Technologies is not only providing modernisation of previous workflows but is also allowing for a reimagining of the way construction projects are designed, planned, built and managed.
When planning a construction project, historically a division existed between spatial (i.e. maps, site plan, design layouts) and non-spatial (i.e. schedule, cost, material) information as stated within a project team or tool. This type of information division often produces redundancy or inconsistency within the construction process. For example, a schedule shows when the structure will be built but does not show where it will be located within a construction site, complicating logistics and site layout.
The advent of modern Geo-Spatial Tech means the division between spatial and non-spatial data is no longer necessary. Data from both categories can now be combined into one unified system. Using today's modern Geo-Spatial Systems, the Project Manager will see "What was built, When was it Built, Where was it Built". This way, Project Managers have an increased Capacity to view and understand the progress of the construction project as a whole.
Geo-Spatial Technologies being used for construction are far more than just providing maps to aid in the process. In fact, they allow a construction company to have an in-depth understanding of the site, any obstacles on site, what utilities are underground, how the site is going to be developed, how the layout should be designed, and many other pieces of information. It allows a construction company to select the best site for their project and build the site to maximise its potential through the best layout design, thus avoiding many financial pitfalls due to unforeseen conditions.
The technology collectively used to collect, interpret, and visualise spatial data through the use of satellite imagery (GIS), GPS signals, IoT sensors, and real-time environmental data feeds creates a rich base on which all decisions for construction will be made. All of this technology relates to each other, and will ultimately provide a better overall understanding of an associated project. At the centre of these technologies is a geo-spatial data platform (LSB or cloud based), which stores the various spatial data layers (land contours/topography and utility line locations) and integrates all the other data associated with the project including project timelines, resource allocations, and risk factors. The resulting product is a unitised project view from which teams can anticipate, circumvent, and plan accordingly for multiple project challenges.
AI is changing the world because it is faster, smarter and predictive. When combined with geo-spatial data, AI can automate so much of the data analysis process that it takes weeks or even months for humans to perform this work in a manual way; therefore, there is tremendous efficiency when using AI, allowing organizations greater productivity. Likewise, AI uses predictive models so that it can see risks or opportunities that might be missing from the analysis done by people.
Risk Assessment and Safety: Geo-spatial systems that utilize AI technology allow for the analysis of historical data with information about the present site to determine any probable structural deficiencies, potential environmental threats, or any safety issues prior to construction. In turn, this decreases the likelihood of accidents and expensive design defects.
Environment and Sustainability: By utilizing spatial data (i.e., terrain, vegetation, drainage, land-use) and AI models to determine how a project will affect the ecology of the area before work commences, teams will be able to plan for flood zones and design their projects to minimize environmental impact — resulting in a greater chance of developing sustainable infrastructure that conforms to local environmental regulations.
Resource Forecasting: AI analytics can assist construction organizations to create forecasts of the amount of resources they will require, when they will need to receive deliveries of those resources, and how to best utilize their labor force so that there is little waste of time and materials, thus reducing costs associated with construction delays. Additionally, IoT sensors and geo-spatial data provide the means for project managers to continuously monitor the amount of resources being utilized and current site conditions in real-time, allowing for modifications to be made in an efficient manner.
The introduction of Digital Twins and Virtual Construction Management: that are among the greatest breakthroughs in creating digital-first approaches to construction. Today, teams utilize a number of sources of geographically-based data as well as Artificial Intelligence (AI) applications to create a digital twin, which is an interactive 3D model that represents the site as it actually exists in the physical universe, allowing for earlier identification, resolution, and coordination of any clashes or discrepancies before actual construction begins. This process greatly reduces errors and increases overall construction quality.
Multiple benefits are realized throughout all phases of construction in part by utilizing geographic data in conjunction with artificial intelligence, including but not limited to:
Reduction of overall project expenditures by improving site selection, reducing rework, and optimizing the allocation of resources.
Improved overall efficiency through faster and more accurate decisions, along with the ability to respond more quickly to real-world site conditions based on data and information available through geographic technology.
Safer projects through greater identification and mitigation of hazards, risks to the environment and structural weaknesses; thereby significantly reducing risk of loss, injury, and liability to the contractor and owner.
The design of infrastructure and/or buildings in accordance with environmental restrictions (sustainability); critical to the success of today's environmentally compliant infrastructure developments and/or green buildings.
Shared source of information for those involved in the project, including architects, engineers, project managers and stakeholders (customers), thus creating a foundation for better communication among all team members.
AI combined with Geo-Spatial Technology is not merely a fad within the Construction Industry but rather something that is foundational. With an ever-increasing volume of Spatial Data (Satellite Imagery, Remote Sensors, Real Time Environmental Data) and the improved and easier accessibility to Artificial Intelligence Tools; here is what we can expect:
Autonomous Systems to Perform Spatial Analysis with Little to No Human Intervention for Planning and Assessing Risk.
Digital Twins for Urban Infrastructure which allow for Predictive Maintenance and Lifecycle Planning Enabled to be Available from the First Day of Use.
Climate Adaptive / Smart Infrastructure that uses Predictive Models to Anticipate Environmental Stressors such as floods, erosion, land use changes, etc.
Integrated Project Management Systems combining Geo-Spatial Layers + AI Analytics + Scheduling + Resource Management in a single environment to yield quicker and more reliable project delivery.
Additionally, the combination of Geospatial/A.I. Technology combined will allow Developers, Engineers and Planners to Adopt Sustainable, Resilient Construction Practices; this is extremely important as Climate Volatility and Increased Urbanization continues to shape our World.
Rapidly evolving urban areas create many challenges. Some of these include an increased amount of Development Area (DA); an increase in the number of Urbanized Areas (UA); an increased number of Development Focus Areas (DFA); the increased complexity of regulatory requirements; the introduction of stricter regulations related to compliance; a growing number of challenges associated with the provision of infrastructure, utilities, and services; and an increased demand for the management and use of resources.
Therefore, the need for an innovative, integrated, and comprehensive approach to construction is greater than ever. Using integrated AI + geo-spatial workflows to address these challenges will provide clarity, improved operational efficiency, and foresight for development across the globe.
Developers can leverage the benefits of integrated AI + geo-spatial workflows early on in the development process to mitigate the risk of cost overruns, optimize infrastructure, and provide for the development of resilient, smarter, and more ecologically responsible structures. For Urban Planners, integrated AI + geo-spatial workflows will provide the tools necessary to be forward-thinking in planning urban growth strategies, improving resource allocation and management, and developing cities designed for the future, not merely for the present.
Understanding the differences between the broader and more specific concepts of geo-spatial technologies and geographic information systems (GIS) will aid in identifying and choosing the correct approaches and tools that may be utilized in the development of infrastructure for the global urban environment.
Geo-spatial is a relatively broad term that captures all forms of geospatial technology, including satellite imagery, remote sensing, and sensor networks. While, as stated, GIS is a type of geo-spatial technology, GIS is a data management system that organizes and presents geo-spatial data in a layered manner. In other words, everything that is in GIS is also geo-spatial in nature; however, not everything that is geo-spatial in nature can be classified as GIS.
The construction industry is experiencing a profound transformation due to the integration of geo-spatial technology and artificial intelligence. Utilizing multiple sources of geo-spatial information, such as satellite imagery and sensors, and combining these sources with GIS technology and enhanced by the power of AI, the construction industry now has access to vast amounts of information, advanced analysis, and comprehensively actionable insights.
The application of AI and geo-spatial technologies is facilitating the elimination of labor-intensive and inefficient tasks within construction and providing companies the opportunity to carry out many of their operations using real-time and predictive data. Also, by being able to better manage risk and plan for sustainability, companies will benefit from lower overall costs because they can allocate their resources more efficiently and mitigate risk more efficiently than before. Due to the rapid evolution of the construction industry, due to increased urbanization, climate change, and more complex construction projects, if companies do not implement AI and geo-spatial technology workflows, they will quickly become uncompetitive in the marketplace. The continuing growth of the construction industry is likely to involve the development of intelligent and data-informed space..
