Future technological trends: A Canadian Perspective from LiDAR CANEX 2024

At LiDAR CANEX 2024, a LiDAR panel of experts from different sectors discussed the latest and upcoming trends and services in 2024. Artificial intelligence was at the top of their list. Have a look at how each expert puts their viewpoint into ongoing AI trends, its competency, and how it is impacting different industries.

Are geomatics and AI a perfect match for the future?

As a matter of fact, the integrated application of AI and geomatics has produced some amazing outcomes in a number of domains, including geomatics. Data extraction and spatial analysis are two excellent examples. Geomatics and artificial intelligence, in my opinion, are an ideal combination. Machine learning with AI may contribute to image classification of satellite photos. Object recognition, such as buildings and rivers, can be completed significantly faster.

Robotics and artificial intelligence are poised to have an immense effect on geomatics. Flying robots such as drones are capable of investigating disaster zones and inaccessible environmental conditions such as wildfires, volcano eruption, earthquakes and floods.

Survey data can be collected from remote regions in unprecedented numbers. That prompts us to make services available in faraway communities.

BIM and digital twins are two more emerging fields that are expected to employ AI. AI-powered visualization and 3D modeling are revolutionizing the infrastructure sector. Making digital twins of cities has the potential to assist in urban planning and help with crucial decision-making. The way we handle natural disasters could be improved by employing 3D interactive models of the earth’s atmosphere.

Undoubtedly, there are restrictions when attempting to apply AI in its infancy. At the moment, the quality of data used for AI algorithms is the main issue with AI models.

It needs accurate information in order to produce the best results. The variety of AI models available in the market is growing. Everyone is attempting to move toward automation.

Are we keeping up with whooping advancement?

Past reports and surveys reflect that organizations, agencies, and municipalities lack location intelligence. Studies show better business outcomes when location intelligence is integrated in a holistic manner. At the same time, it demands a strong commitment to enhance a company’s geospatial skills and its strategy. Adoption of geospatial abilities by organizations comes from leaders who thoroughly understand the extensive capabilities of geospatial data and its applications to get impactful business results.

In Canada, elevation and LiDAR data are widely used for a wide range of applications, including urban planning, mapping and cartography, forestry management, flood modeling, pollution modeling, and transportation planning and many more. In addition, a GeoAI series of automatically extracted imaging data is available in Canada. Machine learning techniques are used to do many data extractions at the same time over the same geographic area.

Canada and the United States have shared a common geometric reference frame for over a century. In 2025, CGS (Canadian Geodetic Survey) intends to adopt the North American-Pacific Geopotential Datum of 2022 (NAPGD2022) and the North American Terrestrial Reference Frame of 2022 (NATRF2022) in parallel with the United States.

With the goal of developing a single reference system for the entire country, CGS is working with the provinces through the Canadian Geodetic Reference System organization (CGRSC), a federal-provincial government organization, to speed up the transition to NATRF2022. This will have a significant impact on future mapping projects.

Various organizations, government institutions, and municipalities are gradually integrating location intelligence into their systems. Universities provide GIS programs, diplomas, undergraduate degrees, and graduations. We need to promote awareness about the real-world benefits of GIS.

This is intended to benefit future students who want to learn and perform research in GIS, as well as more proficient professional geomatics.

Future challenges with AI

With the growing embrace of AI and its societal benefits, we should tackle the issues and risk factors associated with its use. I’d like to mention a few here:

Job displacement caused by autonomous systems and robotics has been a long-standing issue. As AI and automation gets deeply rooted into businesses, we should expect to see it on a larger scale and over a broader spectrum. This can disrupt the socioeconomic balance, leading to disparities.
Bill C-27, known as the Artificial Intelligence and Data Act (AIDA), has been officially passed. AIDA describes a principles-based technique for ensuring proper governance and control over the use of artificial intelligence. I am believe that as we move forward, new restrictions are likely to take its place.
The integration of AI with current systems is extremely important. From interoperability of data, training, and regular optimization of the AI model to keeping up with the changing requirements of organizations, this will create a new demand for AI experts and specialists.
Due to the vast amount of data that AI crunches, there are other possible privacy risks, such as AI systems, and hence their data is compromised, giving sensitive information to hackers. Cybercriminals can use text from language models like ChatGPT to implement and then execute various kinds of scams, giving fake investment opportunities and asking for donations via mediums such as email and social media.
A key component of AI systems is the quality of the data supplied for training. If the malicious actor poisons that data, the model’s outcome will be drastically transformed affecting industries such as healthcare, automotive, and transportation, or perhaps causing more unrest in politically sensitive areas.