Alamanda College in Victoria, Australia, is using Juniper’s wired and wireless solutions driven by Mist AI to transform the networking experience across its campus.
With a network now powered by AI and automation, Alamanda College is able to create a better teaching and learning experience for staff and students, as well as lower the cost of networking deployment and operations through proactive AIOps, predictive recommendations and a Self-Driving Network.
Located in one of Melbourne’s fastest-growing suburbs, Alamanda College has experienced exponential growth since it was founded in 2013 with over 250 teaching staff educating over 3,000 students from preparatory school to Year 9.
To keep pace with the increasing networking demands of a rapidly growing campus, Alamanda College decided to move all of its infrastructure and data to the cloud. With over 5,000 devices now connecting to the campus network daily, a major priority was the upgrade of its wireless network to ensure seamless and high-performance connectivity for users in every part of the school.
Also, as students and staff returned to campus as pandemic restrictions loosened, it was crucial for the college to introduce proximity tracing measures to safeguard the overall health and safety of everyone on campus.
With the continued provision of safe and secure education despite the ongoing pandemic remaining a key priority of the Victorian state government, Alamanda College identified the need to swiftly transition toward a robust and reliable network that was easy to roll out and maintain.
With Juniper’s AI-driven network, students and teachers can now enjoy better digital learning experiences with reliable connections to online learning tools, video and the internet.
“Juniper’s AI-driven solutions have been the perfect fit for our campus environment, enabling us to power a modern learning environment,” said Tony Pace, specialist technician at Alamanda’s eduSTAR.TSS. “With Juniper’s AI-driven network, we have had zero wireless issues and we are able to identify and solve problems that we were not able to detect before.”