• DATA ANALYTICS & MACHINE LEARNING

A proliferation of data collected by devices, sensors, robots, and people will change the way we live and prosper. Data-driven approaches will change the way we design, maintain and renovate infrastructure, and the manner by which we protect the environment.

The advent of the information era creates new needs, new performance requirements, and new threats. It creates also tremendous opportunities for performance optimization, monitoring and efficiencies.

Computational models run at computational speeds that were not considered possible a few years ago, new sensors with new measuring capabilities, next-generation, AI-trained control systems are already change the Civil, Construction and Environmental Industries.

ARGO-E GROUP can help you make sense of complex data by developing powerful visualization tools and analytics platforms. Our solutions enable you to gain valuable insights, track project performance, and make data-driven decisions to optimize your operations and improve project outcomes. Our group works with the entire data lifecycle, from collection, data analysis and then to decision making.

Our dedicated machine learning team leverages advanced algorithms and techniques to unlock the potential of data in the civil, environmental, and construction industries. From predictive analytics to anomaly detection, we develop machine learning models that enhance decision-making, improve risk assessment, and enable intelligent automation for your projects or customized apps.

Through our various initiatives, we have applied Artificial Intelligence (AI) approaches to science data, sensing data, geospatial data, as well as business data with the goal to leverage their full potential, and pave new avenues for the industry and the profession.

Example projects are highlighted below:

Latest Data Analytics & Machine Learning News

ARGO-E GROUP Develops Innovative Python App for Efficient Image Classification for Rock Slope Characterization

ARGO-E GROUP's Machine Learning Division has developed a Python application that assists engineers or scientists without any programming skills, to classify images easily and efficiently. The app was developed as part of a rock slope characterization project in collaboration with Professor Dimitrios Zekkos research group at UC Berkeley, where thousands of photos are used as input and are...


Publication: Using social media to assess earthquake impact on people and infrastructure: Examples from earthquakes in 2018

The content of this page is basically the following paper:  Zekkos, D., Tsavalas-Hardy, A., Mandilaras, G., and Tsantilas, K. (2019) “Using social media to assess earthquake impact on people and infrastructure: Examples from earthquakes in 2018.” 2nd International Conference on Natural Hazards and Infrastructure, 23-26 June 2019, Chania, Greece. You can also download this paper here. Please use th...


VIDEO: Social Media Activity Used to Track Earthquake Activity for year 2018

For the last few years, our research team has been data-mining social media to assess the impact of earthquakes on infrastructure and people. We use machine learning approaches to analyze millions of tweets and tease out the content that is of value to assess the condition of infrastructure following earthquakes. We find that there is valuable content in social media that is posted by users that c...


A review of the role of Unmanned Aerial Vehicles in Civil Infrastructure

Our Founder, Dr. Dimitrios Zekkos has been a leader in data collection and analysis using Unmanned Aerial Vehicles with applications in civil infrastructure. He has authored numerous papers on the topic that can be found here. One of the key papers, published in 2019 is on “Applications of Unmanned Aerial Vehicles in Civil Infrastructure which was published in the Journal of Infrastructure Systems with co-authors Prof. Jerome Lynch and PhD student William Greenwood.