Continuous surveying (to support smart cities, infrastructure, geodesign, and construction) is opening expanded—but unconventional—roles for surveyors and geospatial practitioners.
A member of your field crew that’s a bipedal, survey-rod-carrying robot may be in the distant future, but the work of field data collection has already been affected by robotics, namely in the form of process automation.
This influence will only increase as AEC industries and geospatial professions rise to meet the pronounced global uptick in demand for infrastructure development and modernization. Robotics represents a lot of opportunities to grow the disciplines and professions, but not in the ways we are accustomed to.
Throughout 2018, xyHt has been interviewing key leadership in the geospatial and AEC industries and listening to their keynotes at conferences. The message from each is much the same: the demand for new, updated, smarter, and greener infrastructure cannot be met with legacy tools and methods. Period.
World population growth—without corresponding growth in funding and resources—means we need to work smarter and improve engineering and construction efficiencies. It is not simply a matter of throwing more people at the problem (although we will need more skilled people to support increased project portfolios).
We need practitioners who can work more harmoniously with the “bots”: automated elements, reality-capture technologies, and integrated project-management delivery systems. We’re not just talking about the mechatronic tools like robotic total stations, autonomous UAS, mobile mapping, scanners, and imaging systems. Automation in data analysis, automated feature extraction, applying machine learning and AI—these have steadily made inroads into our workflows, both subtly and dramatically.
For BIM to work throughout a design, construction, and operational cycle, it needs reality capture, accurately and frequently-—often so frequently as to demand the use of not only automated field data collection but also new levels of feature extraction and model updates. Smart construction, like smart manufacturing, needs a constant feedback loop.
The vision of geodesign, the seamless melding of design detail (e.g. IFC BIM models, Revit models, iModels, etc.) in the broader context of geospatial data (GIS) is reaching fruition. An example is the development sparked by the Esri-Autodesk partnership (xyHt, November 2018).
“Continuous representation of reality” is a term that Topcon Positioning Systems CEO Ray O’Connor has described for many years as an all-important element of a successful modernization of the construction industry. What the manufacturing sector has been able to do in automation and modernization for many decades is a holy grail sought for construction, an industry still beset by legacy inefficiencies.
A joint effort between Topcon and Bentley Systems to promote “constructioneering,” a way to remove some of the barriers between the design, survey, and construction processes, promotes a new wave of automation, workflow, and data integration.
The collaboration between Autodesk and Leica Geosystems on the reality-capture software and operation elements of the BLK360 scanning system demonstrates another element of this “bot” future: making the act of data capture simpler and more automated and getting solutions into the hands of more users. In fact, one of our 2019 40 under 40 honorees, roboticist Aaron Morris (who was a lead on that team) has launched a firm focused specifically on feature- and analytics-extraction from this new tidal wave of reality data being generated by these bots and semi-bots.
The advent of continuous surveying is already upon us. The term is gaining broad acceptance in the AEC and geospatial industries, casually referred to in keynote speeches and project presentations at international industry conferences. An excellent summary of the concept is by Durk Haarsma of GIM International (October 2016). The work of developing tools and methods for continuous surveying has accelerated.
In our 2019 Outlook list of outstanding geospatial professionals, we’ve included the profiles of brilliant engineers and scientists working on these solutions. Examples are Spencer Disque of Sigma Space, working on single photon lidar; Jackie Chow, working in sensor integration, camera calibration, and robotic vision; and Yan Fu, a principal scientist with Autodesk working on 3D mesh and other reality-modeling technologies.
Coaching and Conducting
Talk of automation understandably raises concerns for job and career security. No one can sugarcoat the fact that automation in jobs can cause professions to change and can force career changes (or substantial elements thereof).
When faced with what seems to be a relentless paradigm of change, we ask: What’s wrong with simply using our current skills, tools, and methods? And if there is an increase in demand, why can’t we just train more practitioners? That would surely grow our professions. I am quite certain that I could still take on boundary survey work using the analog instruments on my mantle or even topo small sites for design and construction projects.
But our clients and customers are not as nostalgic as we are, and the scale and complexity of such demand will not be sustainable if we maintain the status quo. Through automation, we may reduce hours spent in the mechanical elements of our jobs, but this can free up more people and time for QA/QC, process management, and analysis. If we are not so occupied with the mundane, we are freer to pursue the profound.
Some elements will not change: the professional judgment, experience, and skill needed to evaluate, for instance, boundary evidence or alternatives-analysis to best meet customer desires and needs. There are no magic AI solutions for those elements.
But the very nature of your work may soon change. Practitioners will be called upon to become much more productive—requiring new skills and perhaps a new “digital crew.”
These bots may be able to learn how to recognize patterns in data as they map and process more and more corridors and, through machine learning, raise certainty and reliability in feature recognition and site analyses. However, they need a coach, a conductor.
The critical steps of planning deployment, scheduling, specifying what each team needs to do, the expectations and quality control, these are human elements. The future will hold a lot of opportunity for the skilled and savvy surveyor or geospatial practitioner who leads their human—and digital—teams forward.