BSc, GISP, Associate, Senior Consultant, Information Management
As technology advances, companies will have the opportunity to digitize more. Industries that require the collection, management, and analysis of huge amounts of data, such as environmental, engineering, and construction, stand to benefit as much as any other. With nearly every employee now carrying a computer in their pocket (i.e., their smart phone), collection and access to this data is becoming increasingly mainstream. Mobile data collection is easier than ever, but it wasn’t always this way.
A look at the past of data collection
In the past, data collection on a work site used the traditional pen-and-paper approach. Looking back, not only was this hard work on a wet, windy, or wild day, but it carried with it a certain amount of risk. The risks included losing a sheet of paper, misplacing a note pad, or the potential for illegible notes on mud-spattered pages. Not only that, but it took considerable time to transcribe and analyze notes, enter them into a spreadsheet, and transfer them via e-mail, fax, or even post via courier. The process could take weeks, or sometimes even months.
Things improved with the introduction of clunky, robust laptops and tablets that could be carried on site. Yet, there were still limitations, and given the significant cost and commitment required to create custom electronic tools, many companies didn’t bother. Those who did, benefitted. It was a step forward, but challenges remained such as short battery life, slow operating systems, complex software, and of course the dreaded computer crash where all data was lost. Some of these systems were still in use just 5-10 years ago.
Today’s digitized environment
On today’s worksites progress has been astounding, and now there is a smart phone with numerous apps in nearly every person’s pocket. They’re so ubiquitous, in fact, that we’re often guilty of taking them for granted. Nowadays, when an employee goes out to the field, they can easily record data directly on their phone. Data can even be entered in the most remote of locations, and later uploaded automatically once the phone is back within the cellular network.
Field Program Use Cases
There are many situations in which the digitization of field work can be beneficial. Some examples include:
- Recording geotechnical data for movement or vibration on site.
- Monitoring hydrogeology information such as well-water levels and flow meters.
- Sampling and characterizing soil and vegetation for quality, contaminants, and disease.
- Managing multiple crews and their data during pre-, during, and post-construction phases.
One of Golder’s recent use cases involved a client’s large construction project. A crew was on site, working ahead of construction to record bird nests in trees slated for clearing nearby. The purpose was to gather data on the species of birds in the area that had the potential to be harmed or pushed from their natural environment. This could, in turn, result in delays to construction and damages being paid by the company.
There were many variables for the different bird species. For example, each required a specific no-go radius depending on the specie, some enough to halt construction without mitigations. Workflows were set up so that once a species was identified, relevant SMEs would be notified of locations, safe travel or construction radius, and provided mitigation options by field biologists – all in real time from field to office. This not only meant that birds remained protected in accordance with permitting requirements, but also that there was less likelihood of construction being held up.
Since data was recorded several steps ahead of construction, it allowed situations like this to be dealt with or planned for before physical construction began – reducing costly delays and downtime. In addition, the database provides a record of all locations through time, with the ability to provide proof of due diligence during construction, reducing regulatory risk.
Looking to the future of mobile data capture
As technology and machine learning continue to advance, we expect to see increased savings across the environmental, engineering and construction industries, both in terms of time and costs. Data imaging is likely to play a big role. Machine learning, for example, will be able to scan aerial images and produce ecological descriptions of a location to identify and quantify plant life in the area. Constant recording may also be used on some sites, and machine learning employed to identify passing animal species around the clock with minimal or no human effort, freeing time for SMEs to focus on analysis and decision making.
In general, we can also expect better connectivity in remote locations as cell networks improve. Overall, the capture of data will become easier and faster, with reporting and analytics available in real time, allowing companies to save time and money. Those who put in the effort to embrace these technologies early will reap the highest benefits.