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From Farmers’ Fields to the Frontiers of Space

Machine learning and artificial intelligence (AI) have become buzzwords in the business world. These cutting-edge technologies have the potential to revolutionize industry and help forward-thinking businesses create increasingly innovative solutions that help to improve efficiency, save time and solve some of the world’s most pressing problems.

While these technologies have the potential to revolutionize the workforce, their rapid evolution means that companies need to continually balance the benefits of using them with the risks to their infrastructure and assets. But with proper risk management, machine learning and AI are helping companies to be more innovative, competitive and efficient.

At Calian, innovators are combining applied machine learning and data science with software expertise to add business value to their products and services.

“One of the main benefits of bringing AI and machine learning into our applications is automation,” says Russ Palmer, Vice President of Software Solutions at Calian Advanced Technologies. “Another benefit is the introduction of intelligence, which allows us to make more informed decisions about how to utilize resources or respond to events and become more adaptive.”

Noise Reduction for the Agriculture Industry

One project underway at Calian focuses on developing a noise reduction application for a Calian Agriculture product that monitors grain storage bins. Bin-Sense® uses sensors to detect the level of coverage, temperature and humidity in the bins and provides the information to farmers so that they can monitor their grain.

“We are applying machine learning to enhance the effectiveness of the information from the sensors in the bins,” says Joshua DeJong, Lead ML Developer at Calian Advanced Technologies. “By applying a model to take the information from all the sensors in the bins, we can predict the probability that individual sensor readings are correct, improving the quality of the output, which is meaningful to end users.”

This reduces the effort of having a single operator look at all the readings to find false positives. The model generates a coverage prediction that is more accurate than individual readings. Users have increased confidence in the readings that they are receiving, improving efficiency and reducing waste. It also reduces the number of alerts going out to the farmers, who have more pressing tasks than sifting through alerts that may be false, adds Palmer.

“Leveraging this data to achieve these results almost feels like magic sometimes,” says DeJong, who feels that the agricultural applications of AI and machine learning provide even broader value by addressing food security and reducing food waste and spoilage.

Anomaly Detection and Prediction for the Canadian Space Agency (CSA)

Another project being worked on by the Advanced Technologies team is an automatic anomaly detection project for the Canadian Space Agency. By leveraging machine learning, the project automates the anomaly detection process and reduces the resources needed for routine monitoring and predictive failure analyses. This increases mission availability, delivering more data into the hands of users and saving time and resources for satellite operators.

“Anomaly detection is kind of a fuzzy problem by nature,” says DeJong. “Satellite operators look over reams and reams of satellite telemetry data, looking for anything that's out of the ordinary so that they can determine if the system is misbehaving or is about to misbehave. These anomalies are generally easy for a human to identify and hard for a simple program to identify. But machine learning is really well suited to identifying them.”

Through this project, operators will need to look only at alerts that are automatically raised instead of combing through time series charts filled with data. The technology enables operators to focus on critical alerts and make informed decisions, leading to improved operational efficiencies that have previously been impossible to obtain.

“As we continue to launch satellites by the thousands into space, new missions will require more operations than is available using traditional means,” says DeJong. “This capability will allow our CSA operators to grow the number of satellites in their fleets without exhausting their expert resources.”

AI-Powered Content Generation for Emergency Response

The Advanced Technologies team is also exploring a project to enhance Calian ResponseReady™, the Calian emergency exercise and training platform. Among the many opportunities to employ AI tools, possible applications include using generative AI to help exercise designers create content for realistic simulations and to analyze large datasets resulting from the exercise evaluation process.

A realistic simulation needs to replicate communication pathways that would occur in a real emergency. Exercise designers currently create this content—called “injects”—manually, although they have been introducing some automation to improve efficiency. With recent advances in generative AI, designers are increasingly automating text and image generation and will soon be able to generate videos from text prompts. This provides valuable opportunities to streamline the exercise design process.

“The first thing that we're looking at doing is automating the phone injects,” says DeJong. “Currently, if you want somebody going through the exercise to receive a phone call giving them some targeted information, you must have a control team on standby with a script so that they can call the participants and read the script—that's called a phone inject. We plan to use AI to automatically generate the script and have a text-to-speech service translate it into voice—and even do some interactions and answer some questions as well.” This will save time, increase efficiency and bring even more value to ResponseReady.

AI can also support the exercise evaluation process. During large exercises, evaluators collect qualitative and quantitative data from participants using various evaluation criteria that are tied directly to the exercise objectives. These datasets provide valuable insight for after-action reports but require significant analysis by evaluation staff. AI-supported data analysis can identify trends in quantitative datasets to not only identify key exercise findings but justify these findings with context provided by qualitative feedback.

Broad Benefits of Innovation

These projects highlight the transformative potential of AI and machine learning in various sectors, from agriculture to space exploration and emergency preparedness. By harnessing the power of machine learning and AI, Calian is unlocking new opportunities, enhancing operational efficiencies and delivering innovative solutions to customers.

But this is only the beginning. As these technologies continue to improve their analytical capabilities, they will expand the capacity to provide reliable, actionable and timely information. With users increasingly leveraging these advances across all aspects of society, the capacity to change the world is at our fingertips.