Surveyors today face a rapidly changing landscape as advancements in geospatial technology continue to evolve. With an expanding toolbox of tools and techniques, staying current can be a challenge. Let’s take a look at five key trends shaping the future of surveying, transforming how data is captured, processed, and applied across industries.
In recent years, surveyors have moved far beyond traditional methods like hand-drawn maps and rough visual estimates. Today’s technology allows for precise topographical data collection using advanced laser scanners, drones, and GPS-based systems. For example, fixed-wing drones equipped with laser scanners can cover vast areas and collect high-precision data in a fraction of the time it would take using conventional methods.
However, even with these tools, surveyors often face the challenge of capturing data in hard-to-reach areas where GPS and Wi-Fi signals are weak or nonexistent. Autonomous drones, equipped with SLAM (Simultaneous Localization and Mapping) technology, provide a solution by mapping environments in real-time without needing external infrastructure. Although SLAM systems may offer slightly less accuracy than tripod-based scanners, they significantly improve the speed and efficiency of data collection, especially in complex environments.
This expansion of the surveyor’s toolkit has made the job more flexible, safer, and more efficient, reducing the physical strain on workers and improving workflows.
Artificial intelligence (AI) and machine learning (ML) are revolutionizing surveying by enhancing both data collection and processing. Drones powered by AI can autonomously navigate complex terrains, detect obstacles, and adapt to their surroundings. LiDAR-based SLAM systems, for example, use AI to identify features in real-time, allowing surveyors to capture accurate 3D models without constant human oversight.
In addition to guiding navigation, machine learning improves the quality of data captured by distinguishing between static objects and temporary disruptions, like dust or debris. This refinement process helps ensure that the 3D models produced are accurate and reliable. Once the drone or robot completes its mission, AI can then focus on enhancing the model for final output, making data processing faster and more accurate.
By integrating AI and ML into their workflows, surveyors are gaining new capabilities that streamline operations, increase precision, and reduce human error.
Edge computing, the ability to process data directly in the field, is becoming essential for surveyors, particularly those working in remote or difficult environments. Traditionally, data collected from SLAM systems or other advanced tools would be sent to the cloud for processing, which could lead to delays in analysis. Now, edge computing allows survey teams to process large datasets locally, ensuring that the data is accurate before uploading it for further refinement.
This capability is crucial when capturing and processing complex data like 3D models. Surveyors can now assess the quality of their work in real-time, allowing them to make adjustments or corrections while still in the field, saving time and avoiding costly delays.
Surveying tools are increasingly being used for real-time data collection in emergency situations, such as natural disasters or infrastructure failures. Drones equipped with cameras have proven useful in capturing live video of disaster areas, but they often struggle in low-light or poor weather conditions.
LiDAR-based SLAM systems offer a more robust alternative. These systems can be mounted on drones or ground-based robots to map complex environments like collapsed buildings or underground mines. In such scenarios, first responders can use 3D models generated by SLAM to plan rescue operations, assess hazards, and locate survivors.
Future advancements may allow these models to integrate data from other sensors, such as gas detectors, providing even more comprehensive situational awareness in real-time.
For years, surveying has been driven by the pursuit of millimeter-level accuracy, particularly for applications like construction and infrastructure inspection. Traditionally, tripod-based laser scanners were the primary tool for achieving such precise measurements. However, advancements in SLAM technology and photogrammetry have shifted the focus from extreme precision to a balance between speed and accuracy.
For many applications, such as mapping a structure slated for demolition, survey teams don’t need millimeter accuracy. A portable SLAM platform can capture a 3D model in minutes, rather than hours or days, providing sufficient detail for planning. This streamlined process reduces downtime and allows projects to move forward more quickly, without sacrificing essential data.
As surveying technology continues to evolve, the industry is seeing significant improvements in data collection, processing, and application. The combination of AI, edge computing, SLAM, and more flexible tools is driving the industry toward faster, safer, and more efficient workflows. These five trends are not only transforming how surveyors work but also redefining what’s possible in the field of geospatial mapping, offering greater opportunities for innovation across industries.
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