Garvit Khera’s journey into artificial intelligence began during his school years in India, where a passion for programming quickly evolved into a lifelong pursuit of machine learning and computer vision. After completing a Bachelor’s degree in Computer Science Engineering between 2016 and 2020, he developed an early fascination with teaching machines to “see” and “understand” visual data.
His first professional role was as a Machine Learning Intern, developing a traffic rule violation detection system capable of identifying offences such as missing helmets or illegal parking via image analysis. This experience led to the development of a licence plate recognition (LPR) system, which was an early indicator of the work he would later champion at Park Agility. Following two years with an AI startup, Garvit relocated to Sydney to complete a Master’s in Artificial Intelligence at the University of Technology Sydney, where he discovered Park Agility through the university’s career hub.
Joining Park Agility: Applying AI to Parking Guidance Systems
Garvit joined Park Agility as an R&D intern, drawn by the opportunity to work hands-on with emerging AI technology in a smaller, agile company where he could make a measurable impact. “I’ve always preferred working with companies where I can have end-to-end ownership of projects,” he explained. “At Park Agility, I could see the results of my work in real time and directly contribute to the company’s product evolution.”
Today, Garvit serves as a full-time AI Engineer, responsible for developing and embedding machine learning and computer vision solutions across Park Agility’s smart parking products. His technical focus includes licence plate recognition, image-based vehicle detection, and system visualisation, all core components of the company’s SenseIQ management platform.
Advancing SenseIQ: Turning Data into Visual Intelligence
SenseIQ is Park Agility’s proprietary management platform, which is a comprehensive system that connects, monitors, and visualises sensor data across parking sites. Garvit has been instrumental in enhancing SenseIQ’s internal visualisation capabilities, developing tools specifically designed to help engineering and support teams interpret vast volumes of sensor and system data.
“When you’re working with large data sets, numbers alone don’t tell the story,” he said. “The internal visualisation tools I’ve developed convert complex operational data into clear visuals, helping us identify where sensors, hardware, or software performance can be improved. This allows the team to diagnose issues faster and continuously improve system reliability and efficiency.”
Beyond visualisation, Garvit also develops new functionality in C#, integrating AI-driven modules directly into SenseIQ and improving data accuracy across real-world deployments.
Developing AI-Powered Sensors to Reduce Cost and Increase Accuracy
One of Garvit’s most significant recent projects involves the development of next-generation, individual bay camera sensors capable of detecting vehicle presence using multiple AI algorithms at the edge. While Park Agility already offers a high-accuracy hybrid solution that combines LiDAR and camera technology, itself still a niche capability within the parking guidance sector, Garvit is now focused on delivering a camera-only solution that achieves comparable accuracy.
“Our goal is to develop a standalone camera sensor that delivers the highest possible accuracy while reducing cost by up to 30–40% per unit,” Garvit explained. “The sensor captures images every few seconds, analyses occupancy, and records metadata such as licence plates and vehicle type, all using a lightweight AI model optimised to run on a small embedded chip.”
Achieving near parity with LiDAR‑assisted accuracy using only cameras would represent a major value addition to Park Agility’s sensor portfolio, enabling wider deployment in price‑sensitive environments and further differentiating the company from other parking guidance system providers.
Precision and Privacy: Building Smarter, Safer Systems
Garvit also led the integration of high-accuracy licence plate recognition (LPR) within SenseIQ™, achieving 99.5% plus levels of accuracy across deployments. In addition, he engineered an AI-powered privacy compliance feature that automatically blurs individuals in captured images, ensuring compliance with Europe’s GDPR regulations and reinforcing Park Agility’s commitment to responsible data management.
“All images stored in our database are automatically processed to remove identifiable human features,” he noted. “It’s not just a technical requirement. It’s about building trust with customers and end users.”
Balancing Technological Progress with Real-World Application
Artificial intelligence evolves rapidly, often outpacing commercial product cycles. For Garvit, bridging this gap means focusing on practical AI solutions that work reliably in constrained environments, such as embedded chips with limited memory.
“Much of today’s AI advancement is in generative AI, but our focus is on classical machine learning and computer vision,” he said. “These technologies make our systems more reliable, faster, and adaptable to real-world deployment.”
He also sees potential for generative AI in automating internal processes, illustrating how Park Agility continually explores efficiency improvements across both product and business operations.
A Culture of Innovation and Ownership
Garvit credits Park Agility’s culture for fostering his professional growth. “There’s no micromanagement,” he said. “Brad and the leadership team give me full autonomy to design, test, and implement solutions. When I present findings, they listen, provide support, and trust my recommendations. That level of ownership motivates me to do my best work.”
The collaborative environment, hybrid work flexibility, and clear focus on innovation make Park Agility a standout in Australia’s technology landscape.
Delivering Accuracy, Equity, and Access
At its core, Park Agility’s mission is to make cities and commercial facilities more efficient and accessible through precise, data-driven parking guidance systems. Garvit explained how the company’s bay-level accuracy (a camera sensor per parking bay) enables unique operational advantages.
“Some competitors use one camera to monitor multiple bays, which reduces accuracy,” he said. “With Park Agility’s system, each bay can have its own camera, providing unmatched precision. It allows asset owners to account for every transaction and ensure equitable access to parking spaces.”
The technology also supports better compliance and fair use. For instance, it can automatically identify employees parking in restricted customer zones or unauthorised vehicles occupying EV or disabled bays—ensuring systems function fairly for all users.
Looking Ahead: The Next Era of Smart Parking
As AI becomes more cost-effective and embedded systems grow more powerful, Garvit sees the technology becoming both smarter and more accessible. “In the next five to ten years, sensors will be cheaper, more efficient, and widely adopted,” he said. “This will lead to better-managed facilities and more equitable access for everyone.”
The vision extends beyond convenience, toward reshaping urban mobility and reducing congestion through intelligent, data-led infrastructure.
About Park Agility
Park Agility is a leading provider of intelligent parking solutions across Australia. The company specialises in parking sensors, guidance systems, and integrated signage that help councils, property owners, and operators improve parking turnover, compliance, and user experience.
With a focus on accurate data, seamless integration, and responsive customer service, Park Agility supports clients ranging from local government to shopping centres and public facilities.
If you are considering how to improve parking efficiency and compliance in your facility, Park Agility can help. To learn more about their solutions and explore how they can support your organisation, get in touch with the Park Agility team today on +61 2 8488 3333
