When the initial impacts of COVID-19 hit earlier this year, DeepSense executive director Jennifer LaPlante wanted to help ocean sector companies.

The Data Analytics Readiness project was quickly launched to provide supplemented resources and support to help companies in a challenging economic climate and prepare them for future opportunities.

“We wanted to do something to help small and medium sized ocean sector organizations through these difficult times,” says LaPlante. “Many companies I meet are ideal candidates for complex projects but are not quite there with their data. Through providing some support now, this program enables companies who might not otherwise be ready for a DeepSense project to get there more quickly.”

Based out of the Faculty of Computer Science, the DeepSense innovation environment enables ocean related companies to connect with data and ocean scientists to leverage artificial intelligence and machine learning in developing commercially useful predictive models, analytical prototypes, and applications for use in the ocean economy.

Advancing data capabilities

Since launching in April, the project has supported 9 ocean companies grow their data capabilities.

Organizations including Kraken Robotics, Sedna Technologies and Pisces RPM Inc. have benefitted from short term projects which included student workers. Project areas covered range from preparing governance, processes and documentation for how current or future data is collected and stored, to creating and modifying databases to improve scalability as organizations grow and add new data sources. 

“Many small companies target their resources and investment on technology that has an immediate impact to their customers and data can often be seen as a cost versus a differentiator or enabler. However, all companies generally have a lot of data that could be used to their advantage,” says LaPlante. “This is where DeepSense students can come in and not only help companies define data projects but provide the resources to more easily advance digital capabilities.”

LaPlante hopes this short-term initiative will help companies not only during COVID-19 but longer term.

“By maximizing their data now, companies are in a better position to complete more complex analysis in the future,” she says. “When data is well structured and organized, companies can more easily explore artificial intelligence, machine learning, or data visualization projects which can really take operations or product development to the next level.”

Opportunities for students

Recognizing that it’s not only companies who have been affected by the impacts of COVID-19, the project has provided co-op and internship opportunities for 14 students from across local institutions including Dalhousie and NSCC, while connecting companies with needed staffing.

For Dalhousie student Milap Bhanderi, the project has provided him with an internship in an uncertain job market and the opportunity to explore a new industry through his work leveraging marketing data for Kraken Robotics.

“When I started my internship with Kraken, I had no clue about the ocean sector and its technologies but as I am working with one now, I am more curious to know everything about it,” says the Master of Applied Computer Science student. “There are vast opportunities in the ocean sector for students like me where they can put their best foot forward and help companies in the advancement of ocean technologies through machine learning, data science, artificial intelligence and UI/UK skills.”

“Like Milap, many of the students we partner with are international and had never considered working in the ocean sector,” says LaPlante. “The project has given them support and mentorship and provided them with opportunities as they struggled to meet their program requirements.”

As the 2020 summer project comes to an end, LaPlante is hopeful that participating companies will be able to explore complex machine learning projects in the future and more students will seek out the vast potential of a career in the growing ocean sector.