C+S November 2020 Vol. 6 Issue 11(web)

The Future: Advancing Our Work What does the future for wetland science technology entail? The pos- sibilities are endless, but one thing that is certain, says Schlicht, is that technology will continue to advance the work of wetland scientists and environmental engineers in a way that nothing else could. A couple of exciting new technologies to watch are Esri’s ArcHydro Wetland Identification Model (WIM) and advances in drone deployment with paired software like Esri’s Site Scan for ArcGIS for compiling photos and video for preliminary wetland assessments and monitoring. “Ecobot is going to open the door for us to be able to collect data more efficiently and effectively. The result is providing much better and more high-quality reports back to our clients and in a real-time fashion as well.” About Ecobot Ecobot empowers the AEC and environmental consulting industry to better serve their clients by reducing the time and expenses required to complete environmental regulatory reporting. The field scientists in these industries make critical decisions that inform land use and Eco- bot’s wetland management platform provides accuracy and efficiency for thousands of wetland delineation reports submitted to the USACE each month. See how Ecobot can transform your natural resources consulting workflow at ecobotapp.com.

maps along with the best aerial he could find and literally drawing dots on the map to indicate wetland boundaries. “We’d bring that back and hand it to our GIS person and they would try to replicate it,” he recalls. A few years later, handheld GPS devices were introduced. Now, GPS and GIS technologies have been integrated into software applications: like Ecobot’s partnership with Trimble and Ecobot’s integration with Esri’s ArcGIS mapping capabilities. “Simply being able to pull up a map on my smartphone makes a really big difference,” says Durish. Introduction Previously in this series, we reviewed the importance of data man- agement behind the model handoff during BIM lifecycle implementa- tion, in terms of data interoperability, accuracy, and sufficiency. We highlighted the necessity of developing well-defined data requirements from an Asset Management / Facility Management (AM/FM) perspec- tive and using them to regulate delivery phase data collection and pop- ulation. We also described an AM/FM Data Dictionary Management System (DDMS) that helps address commonly-seen issues which oc- cur during the Project Information Model ( PIM) to Asset Information Part 4: A Cradle to Cradle Digital Twin Ecosystem for Building Asset Management Continued from PARTS 1, 2, and 3 By Dr. Eve Lin, Dr. Xifan (Jeff) Chen, and George Broadbent New Era of BIM Lifecycle Implementation

LEE LANCE is Co-Founder and CEO of Ecobot. Contact him at lee@ecobotapp.com.

Model (AIM) transition as well as during operations and maintenance. This article further discusses the data flow during the entire project lifecycle from delivery to the operational phases and introduces the current trend of Digital Twins – an ideal BIM implementation scenario that needs to be built on top of a solid data foundation. BIM Lifecycle Data Management As discussed in a previous article, Figure 1 illustrates the top-down structure of a project lifecycle from different levels. It illustrates the fundamental importance of a well-defined and managed FM-oriented DDMS to the entire BIM program. While we emphasized the impor- tance of a DDMS during the FM stage because of its long duration, and high operational cost during the entire lifecycle, a well-planned DDMS is a critical foundation to support BIM lifecycle data management. In the real world, even a well-coordinated data management plan could collapse at any moment due to small data glitches in the data exchange process and consequently impact the downstream data flow. Without certain governance and policies to standardize the workflows and pro- cesses, it is hard for organizations to maintain data interoperability, sufficiency, and accuracy because teams and individuals tend to work in silos and make decisions based on available information.

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