At Cognitive Systems, our Wi-Fi Sensing technology, WiFi Motion, transforms ordinary Wi-Fi signals into a powerful awareness platform—detecting motion, understanding patterns, and providing insights into what’s happening at home. But while the magic might seem to happen on your device, there’s an invisible backbone making all this possible: our cloud infrastructure. Every motion detection, every app alert, and every insight your phone receives is supported by a carefully engineered cloud environment that connects, manages, and evolves with each deployment. In this post, we’re giving you a behind-the-scenes look at how our cloud team makes this all work—from the first conversation with a customer to ongoing improvements months down the road.
Why Cloud Infrastructure Matters for Wi-Fi Sensing
Wi-Fi Sensing works by detecting motion through connected devices like your home’s Wi-Fi router or a smart speaker, such as a Google Mini. But delivering that motion data to your phone reliably and in real time isn’t as simple as sending it directly from the router. Most phones block incoming connections from routers due to firewalls and security policies—and even if they didn’t, the connection wouldn’t be stable enough to count on. That’s why we’ve built WiFi Motion on a hybrid edge-cloud architecture. All motion detection happens locally on the edge (e.g., the router), ensuring fast, private, and reliable response times. Meanwhile, the cloud handles user-facing tasks like motion notifications, live motion views, and insights—acting as a secure bridge between the router and your mobile device.
Our cloud infrastructure acts as the sensing system’s translator and traffic controller—receiving motion data from the router, processing it, and securely sending alerts and insights to users, even if their phone isn’t on the same network. Real-time motion is first detected and processed locally by the router. When a motion event is triggered, it’s sent to the cloud, where it’s further processed and securely routed to your phone—even if you’re away from home. This division allows for efficient, scalable integration. Security is built in at every step, with TLS encryption, unique device certificates, and AWS-backed encrypted cloud storage to meet global privacy standards. Our infrastructure is designed to scale without sacrificing performance. We use Kubernetes, specifically Amazon EKS, to manage global deployments efficiently (you can read the full blog on how we use AWS on their blog). This ensures that end users get a fast, reliable experience with low-latency motion alerts and seamless updates. For our partners and customers, it means faster rollouts, region-specific service delivery, and infrastructure that grows with their business.
From Idea to Live Deployment: How We Bring Wi-Fi Sensing to Life
- Initial Request & Discovery: Everything starts when a client expresses interest. Our cloud team immediately engages to understand their goals, infrastructure, and user needs. We assess motion detection thresholds, data sources, privacy requirements, and integration points like custom APIs or app interfaces. Compliance needs and regional data handling requirements are also identified to ensure alignment with regulations.
- Configuration & Planning: With requirements defined, we design a deployment architecture tailored to the client’s environment. This includes defining alert logic, motion sensitivity (e.g., pet filtering), and UI preferences. We map data flows, set thresholds, and prepare a security model that governs data storage, access, and retention—ensuring regulatory and performance compliance from the outset.
- Cloud Instance Setup: We use Helm to deploy a dedicated cloud instance within Kubernetes, provisioning all necessary components: load balancers, messaging queues, backend services, and databases. Kubernetes pods are configured for key functions like motion processing, connection management, and alert delivery. Helm ensures consistency across dev, staging, and production environments, making the infrastructure scalable, secure, and client-specific.
- Development & Iteration: Once live, the system enters a testing phase where we validate real-world behavior and optimize accordingly. We simulate motion events, test UI responsiveness, and tune cloud-side alert logic. Integration with client hardware (e.g., routers, IoT devices) and software (e.g., dashboards) is verified, with issues quickly resolved through iterative feedback loops.
- Pilot Launch: When ready, we launch a production-ready Kubernetes cluster via our Pilot tool. It applies all configurations and deploys the instance into a selected AWS region for low-latency performance. Real-time monitoring ensures the full motion-to-alert pipeline operates reliably at scale, with built-in observability for debugging and analytics.
- Ongoing Maintenance & Feature Delivery: Post-launch, we provide continuous monitoring, automated log management, and proactive system updates. Kubernetes’ self-healing ensures uptime, while our continuous integration and continuous delivery (CI/CD) pipeline enables rapid rollout of new features and fixes. The system can scale horizontally to meet growing demand without interrupting service or performance.
What sets our process apart is how easily it fits into existing ecosystems. We don’t force a one-size-fits-all platform; instead, we work with the customer’s infrastructure and adapt to their stack. Whether they need APIs, regional routing, or unique cloud configurations, our system is designed to integrate smoothly and evolve alongside their roadmap. By planning each deployment with future updates in mind, we make it easier to introduce new features down the line—avoiding rework, delays, or breaking changes. It’s a forward-compatible foundation that scales with our partners’ ambitions.