
Discreetly monitor Wi-Fi activity
In an ever-evolving technological landscape, organisations must be agile and innovative to maintain security. As part of our commitment to revolutionising the way people harness data, we’ve been working on a unique challenge: enabling our clients to discreetly monitor Wi-Fi activity in secure areas without incurring the high costs typically associated with large or complex IoT devices. The result? A small, lightweight solution, built on a commodity compute, that streams data into the Elastic stack—all seamlessly integrated and deployable within AWS.
Identifying the Need
Our client, an organisation with multiple secure facilities, was in need of a solution capable of monitoring Wi-Fi devices without alerting unauthorised users or overcomplicating operations. Off-the-shelf products were considered too bulky, overly complex, and cost-prohibitive for widespread deployment. At NIAXO, we pride ourselves on our people-centric approach, so we tailored a solution that was as user-friendly and scalable as it was discreet and cost-effective.
Our Innovative Approach
The NIAXO team chose a small board computer (SBC) as the device foundation due to its compact form and versatility. By installing Linux, a robust operating system with good security capabilities, we gained the flexibility to develop a custom sniffer application that could capture Wi-Fi data in real time. From there, we integrated this data pipeline into AWS, leveraging services such as AWS IoT Core for secure device management. The data was then pushed into Elastic, allowing for intuitive dashboards that provided immediate insights into network usage.
Streamlined Deployment and a Successful Outcome
The team completed multiple device deployments across a controlled zone, verifying that each device discreetly monitored and consistently logged Wi-Fi activity, streamed the data to AWS services, and displayed insights within the Elastic dashboard. A solution that drove tangible results and achieved the client’s key objective—to gather real-time data efficiently and securely