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Cover image for New Project Launch(Q3): SparkleNET Corridor
New Project Launch(Q3): SparkleNET Corridor Guardian 🛡️⚡ Just published our latest build at SparkleNET, the Corridor Guardian, an autonomous Edge AI infrastructure monitoring and threat triage system designed for trade corridor security. When securing physical infrastructure and trade routes, cloud-processing delays simply don't cut it. We built a localized telemetry pipeline that ingests, triages, and visualizes live threat data with sub-70ms latency. Key Highlights: * Sub-70ms Response: Edge nodes handle anomaly detection locally with minimal transit overhead. * Resilient Architecture: Continuous fail-safe logging, even during WAN network disruptions. * Tech Stack: Python, Edge AI, n8n, Docker, Caddy, and a clean Tailwind CSS live dashboard. Check out the full breakdown and system architecture on my profile! 👉 Live Demo: https://sparklenet.space/dashboard/index.html https://sparklenet.space/Portfolio.html
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Cover image for I’ve been building SabiFlow for
I’ve been building SabiFlow for a while, and honestly, the most interesting part of the project isn’t the code. It's the problem. Because it's personal. I've experienced that thing where money comes in and somehow, without you really noticing, it starts disappearing. Not because you don’t earn enough. Not necessarily because you're irresponsible either. Sometimes money simply has no job when it arrives. And as an engineer, that got me thinking: What if the problem isn't budgeting? What if the problem is that we’re asking people to make too many good decisions at the exact moment they have the most temptation to make bad ones? That question became the foundation for SabiFlow. Instead of telling someone, "You should save 20% of your income," I started thinking about what would happen if the system simply helped assign every inflow a purpose the moment it arrived. That led me down a rabbit hole. Funnels. Automated distribution. Wallet infrastructure. Virtual accounts. User behaviour. Transaction flows. KYC. Compliance. Even the psychology behind notifications. And this is probably my favourite part of being both an engineer and a founder. I don’t just ask: "How do I build this feature?" I ask: "Why does this problem exist, and what kind of system could make dealing with it easier?" Then the engineer in me comes along and asks: "Okay… but how do we actually make this work reliably?" 😂 That tension between the founder thinking about the problem and the CTO thinking about the system is probably what I enjoy most about building SabiFlow. I’m still figuring a lot of it out. But I'm curious: What’s a problem you’ve experienced personally that eventually made you want to build something around it?
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Cover image for Technology has always been where
Technology has always been where my passion lies. Although I spent the past year working outside the tech industry, the experience reminded me that my true passion is building technology that solves real-world problems. Today, I'm excited to fully recommit to my journey as a software developer. My experience includes: 💻 Web Development 📱 Flutter Mobile Development 🤖 AI Applications 🧠 Data Analysis, Machine Learning & Deep Learning Some of the projects I've built include: • AI Email Response Generator • Traffic Sign Recognition System • Child Tracking System (Flutter, Firebase, GPS & IoT) • Responsive web applications I'm currently open to software development, AI, and mobile development opportunities where I can contribute, learn, and grow. If you're hiring or know of any opportunities, I'd love to connect. 🚀 Explore my portfolio: My Portfolio Website (https://ekumachidinma.netlify.app/)
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Cover image for SparkleNET Corridor Guardian: Edge Telemetry
SparkleNET Corridor Guardian: Edge Telemetry & Object Detection Prototype Project Overview & Engineering Objective The Corridor Guardian is a lightweight, edge-computed telemetry sandbox designed to simulate real-time object detection and status monitoring completely offline. Engineered to test high-resilience IoT and data pipelines without relying on continuous cloud connectivity, this prototype highlights zero-latency systems architecture at the edge. Technical Architecture & Implementation * Sandbox Environment: Deployed a local 1-Node Lab Sandbox utilizing Termux running directly on an Android device for hardware-agnostic edge simulation. * Messaging & Communication Protocols: Integrated MQTT messaging pipelines to handle low-overhead telemetry ingestion and real-time event dispatching. * Workflow Automation: Leveraged n8n data flows to orchestrate asynchronous data routing and local event-handling loops. * Edge Scripting & Directory Mapping: Programmed a custom Python edge-loop script that maps local directory trees to simulate live object detection telemetry streams under completely offline conditions.
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