The Internet of the Built Environment

Posted on December 5, 2019 by lidar
ASCE's image for the Internet of the Built Environment

The Internet of the Built Environment

One of the key drivers, along with mobility, on demand services, 5G and more, of the digital transformation of society is IoT – the Internet of Things. The plan for IoT is to have a sensor on everything, from bridges to your refrigerator, that can communicate the desired information in real time. IoT is supposed to put the Smart  in Smart Cities.

I have never really liked the “things’ part of that concept. It seems like Kevin Ashton, author of the very valuable “How to Fly a Horse” and coiner of the term wasn’t quite sure what he wanted to say. No doubt he wanted it to be flexible so that IoT would stand the test of time, which it has, but I would like to suggest an update, or maybe a more specific category which I think better describes what really needs to be done.

I believe we need to monitor and/or instrument the Built Environment. Those are the “things” that as a civil engineer that I am interested in. People have already instrumented the natural environment and they are welcome to classify that as they see fit. The NSF’s NEON comes to mind.

So I would like to propose the IBE – the Internet of the Built Environment. Transportation facilities, buildings, utilities, vehicles, UAVs and more all need to be connected and integrated into a master control and monitoring system, not unlike what NEON is doing for the natural environment.

Continue reading →

Posted in 3D Modeling, AI, artifical perception, artificial intelligence, Autonomous vehicles, BIM, Civil Engineering, Data, Digital Transformation, driverless vehicles, Drones, Environmental, GIS, Government, Infrastructure, intelligent cities, Internet of Things, Sensors, smart cities, Software, Standards, UAS, UAVs, Young Geospatial Professional | Tagged , | Leave a comment

Daimler Testing Autonomous Mercedes in California

Posted on December 4, 2019 by lidar
Photo of Daimler is Testing Robo Taxis in San Jose.

Daimler is Testing Robo Taxis in San Jose.

Daimler is testing autonomous taxis in the U.S. despite new CEO Ola Kallenius saying that the automaker will “rightsize” its spending level on self-driving technologies.

Daimler’s autonomous-driving technology will more likely be apply to commercial vehicles for freight companies on long haul routes than taxis, Kallenius told journalists at the company’s investor day in London last month.

The company has started self-driving taxi tests in California to gather user feedback, people familiar with the matter told Automotive News Europe.

“We have not put the project on ice. We are looking at where we can improve efficiency and gain synergies so we don’t unnecessarily duplicate or triplicate our development work,” said one of the people. “This pilot program is about capturing the user experience.” Continue reading →

Posted in AI, artifical perception, artificial intelligence, Autonomous vehicles, Business Development, computer vision, driverless vehicles, Research | Tagged , , , , | Leave a comment

Sensor Fusion Makes Sense for Autonomous Vehicles

Posted on December 3, 2019 by lidar
Image of Sensor Fusion for Self Driving Vehicles

Sensor Fusion for Self Driving Vehicles

The automotive industry remains divided on the sensor configuration needed to support autonomous driving. Tesla is resolute that cameras and radar systems will be sufficient, yet both systems have their shortcomings. Harman, a Samsung company believes safe automated and autonomous driving can only be achieved by combining LiDAR (Light Detection and Ranging), radar and cameras in a sensor fusion design.

Just Auto recently interviewed Robert Kempf, Harman’s vice president in ADAS/automated driving, on how it’s overcoming today’s LiDAR issues with recently-launched solid-state LiDAR technology and why the merging of this data in the ECU architecture is key to its success.

Appropriate sensor topology for autonomous driving is a highly debated topic. What is Harman’s current stance? 

There is much discussion and Harman is of the opinion that to support the quality and diversity of information required in automated and autonomous driving, a combination of LiDAR, radar and cameras is the optimum. Each offer advantages and disadvantages, so the successful fusion of the data sets provided by these sensors is imperative for a robust solution. Continue reading →

Posted in AI, artifical perception, artificial intelligence, Autonomous vehicles, Business Development, computer vision, Consumer, driverless vehicles, Laser Scanning, Lidar, point clouds, Radar, Research, Safety, Sensors, Software, solid state, solid state lidar | Leave a comment

Scan to BIM – How to Deal with Real World Imperfections

Posted on December 2, 2019 by lidar
graphic of Scan to BIM in the Real World

Scan to BIM in the Real World

Thanks to Dan Edleson for this third guest blog post discussing the imperfections that need to be recognized in the real world of Scan to BIM.

“If the world were perfect, it wouldn’t be.”

– Yogi Berra

The great thing about Revit is it makes it easy to be a perfectionist. When I sketch, I am often inclined to draw loose, rough lines. This is fine for conceptual work but doing documentation by hand has often frustrated me. I was never a fan of the T-Square in college and only used my Mayline once before I started producing all my projects in AutoCAD and tracing over them to get clean, straight lines on my hand drawings.

Revit takes AutoCAD’s perfect straight lines to the third dimension, which is great for a typical project, but can be problematic when the existing conditions you are modeling have several decades of warping that need to be documented. If you don’t have the funds to purchase an expensive plugin, you can still quickly and accurately document these imperfections in the built environment using some of Revit’s advanced modeling tools. Let’s look at how to model out of plumb walls, multi-sloped roofs, and warped floors. Continue reading →

Posted in 3D Modeling, BIM, Construction, Data, Feature Extraction, Laser Scanning, Lidar, point clouds, Quality, Software | Tagged , , , , , , , | Leave a comment

Thermal Imagery Can be Collected with a Drone

Posted on December 1, 2019 by lidar
point cloud image Thermal Imagery Captured with Drone

Thermal Imagery Captured with Drone

This ARE Corp. blog post introducing the use of thermal imagery was written by Andrew Mallin, UAS/GIS Solutions Specialist.

Our clients face various challenges and to help them make informed decisions, ARE Corp. flies a variety of sensors onboard our UAS platforms. Today, we’ll be addressing the applications and benefits of aerial thermal imagery.

At ARE, we fly near-infrared thermal cameras that measure infrared radiation, or infrared light. This electromagnetic radiation is invisible to the human eye and only sensed by humans as heat. Continue reading →

Posted in 3D Modeling, Business Development, Drones, Environmental, Mapping, remote sensing, Sensors, UAS, UAVs, Visualization | Tagged , , , , | Leave a comment

Agricultural Drone Best Practices and Lessons Learned

Posted on November 30, 2019 by lidar
Image of GSD Agricultural Drone Best Practices

Agricultural Drone Best Practices

Reaching data accuracy on your experimental fields requires that you fly the right drone, at the right time, with the right settings. It is easy, but needs a little bit of preparation. In this guide, we will walk you over the basics of agricultural drone configurations, from your optimal GSD based on your desired traits, to the ideal weather conditions as well as other tips to get the perfect scouting maps and analytics.

If you currently fly drones on your experimental fields to measure plants count or other plant characteristics such as plant height or flowering, or if you’re just exploring the drone-based aerial phenotyping world and you’re unsure which type of drone to choose from, then this guide is right for you. Continue reading →

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A Detailed Evaluation of Uncrewed UAS Lidar

Posted on November 29, 2019 by lidar
Point Cloud Image for Uncrewed UAS Evaluation

Uncrewed UAS Evaluation

Uncrewed aircraft systems (UASs) with integrated light detection and ranging (lidar) technology are becoming an increasingly popular and efficient remote sensing method for mapping. Due to its quick deployment and comparatively inexpensive cost, uncrewed laser scanning (ULS) can be a desirable solution to conduct topographic surveys for areas sized on the order of square kilometers compared to the more prevalent and mature method of airborne laser scanning (ALS) used to map larger areas.

From a paper by Babbel, et. al.

This paper rigorously assesses the accuracy and quality of a ULS system with comparisons to terrestrial laser scanning (TLS) data, total station (TS) measurements, and Global Navigation Satellite System (GNSS) check points. Both the TLS and TS technologies are ideal for this assessment due to their high accuracy and precision. Continue reading →

Posted in 3D Modeling, airborne LiDAR, Data, Drones, GNSS, GPS, Laser Scanning, Lidar, Mapping, point clouds, Quality, remote sensing, Research, Sensors, Software, Surveying, topography, UAS, UAVs, Young Geospatial Professional | Tagged , , | Leave a comment

Footwear as Evidence – Documenting in 3D

Posted on November 27, 2019 by lidar
photo of crime scene Footwear as Evidence

Footwear as Evidence

Imprinted in sand, moulded in dirt, or stamped on the floor—footprints discovered at crime scenes can provide evidence for forensics teams who play a vital game of whodunit. In a two-dimensional form, the footwear evidence can be flawed at best. With the use of a FARO scan arm, laser points, and CloudCompare, these simple prints become three-dimensional models which forensics teams, police agencies, and analysts can use to build the profile of a criminal.

From an article in the Medium by Daniel Reale and Hayden Mak

In March 2019, UTM Forensic Science student Charmaine Rodrigues published an article with instructor Eugene Liscio about how she and Liscio used a FARO Scan Arm to capture footwear impressions and analyze the impressions in CloudCompare.

“FARO has revolutionized all these areas in [terms of] what we can do,” says Eugene Liscio, an instructor at UTM and a 3D forensic analyst. The areas include documentation of forensic evidence, analysis of findings, and visualization of reports, areas that his company, AI2-3D, specializes in. Continue reading →

Posted in 3D Modeling, 3D Printing, Data, Forensics, Hardware, Indoor Mapping, Laser Scanning, Metrology, point clouds, Research, Sensors, Software, Surveying, Visualization, Young Geospatial Professional | Tagged , , , , , , | Leave a comment

Forensic Laser Scanning Applied to the Mining Industry

Posted on November 26, 2019 by lidar
photo of Forensic Laser Scanning in the Mining Industry

Forensic Laser Scanning in the Mining Industry

This paper on forensic laser scanning comes from researchers at the Southern African Institute of Mining and Metallurgy.

Background

In the South African mining industry, great emphasis is placed on creating a safe, healthy, and productive working environment. Fatalities have a major impact on the perception of mining as a career and are detrimental to the image of the industry as a good and safe working environment. All mining companies have embarked on focused risk management programmes. The occurrence of serious incidents and related fatalities is, however, still unacceptably high, and more emphasis should be placed on strategies in order to be able to achieve the ‘zero harm’ goal adopted by all South African mines. History has proved that fatalities are ‘cyclical’ in nature. Bad periods are often followed by good periods due to the subsequent intense attention to improving adherence to standards. However, the aim is to minimize these cycles and pursue a real drive towards zero harm. Here, the use of laser technology in incident investigations can play a significant role. Continue reading →

Posted in 3D Modeling, Forensics, Laser Scanning, Lidar, Mapping, Research, Young Geospatial Professional | Tagged , , | Leave a comment

DARPA is Testing Military Drone Dragnet Program

Posted on November 25, 2019 by lidar
Sketch of DARPA Testing Drone Dragnet

DARPA Testing Drone Dragnet

When the Pentagon’s Defense Advanced Research Projects Agency – DARPA tested an “Aerial Dragnet” system for tracking drones over urban terrain last month, Echodyne lent a helping hand.

Echodyne — a Kirkland, Wash.-based startup backed by Microsoft co-founder Bill Gates — provided the compact radar systems for DARPA’s tests during the week of Oct. 23 in the San Diego area, in conjunction with the University of Washington’s Applied Physics Laboratory. Continue reading →

Posted in Admin, Business Development, Drones, Government, Radar, Research, Robots, Security, UAS, UAVs, Visualization, Young Geospatial Professional | Tagged , , , , , | Leave a comment