• Start Anomaly Detection in IoT with Less Data

    This is a question I get a lot, and I like it because it clears up a common misunderstanding. You do not need massive data volumes to start using ML for IoT anomaly detection. Let me explain it in a grounded, practical way. Short answer (plain and honest) For anomaly… Read More ⇢

    Start Anomaly Detection in IoT with Less Data

  • AI and ML in IoT, Explained Without the Jargon

    When people hear AI, ML, and IoT together, it can sound heavier than it really is. I like to break it into roles. Who does what, and why it matters. Let’s start with the basics. What IoT does on its own IoT is about sensing and reporting. Sensors collect data.Devices… Read More ⇢

    AI and ML in IoT, Explained Without the Jargon

  • The Key Differences: Favoriot’s Rule Engine 2.0 and AI Agents

    Why Rule Engine 2.0 Feels Like an AI Agent When you look at Favoriot’s Rule Engine 2.0, you see things that resemble agent behaviour: At a glance, that sounds agent-like. But under the hood, it’s doing something very different. What Rule Engine 2.0 Actually Is Rule Engine 2.0 is a… Read More ⇢

    The Key Differences: Favoriot’s Rule Engine 2.0 and AI Agents

  • The Role of Machine Learning in IoT Systems

    The Internet of Things has moved far beyond simple device connectivity. Early IoT deployments focused on collecting data and displaying it on dashboards. As deployments scaled, this approach revealed its limits. Large volumes of sensor data quickly outgrow manual analysis and static thresholds. Machine learning addresses this gap by turning… Read More ⇢

    The Role of Machine Learning in IoT Systems

  • Favoriot’s Rule Engine 2.0: A Structured Approach to IoT Automation

    Rule Engine 2.0 is a visual, node-based automation framework designed to simplify the creation of IoT workflows. It enables users to define how data is received, evaluated, processed, and acted upon using a clear graphical interface rather than custom code. Instead of writing scripts, users assemble workflows by connecting nodes,… Read More ⇢

    Favoriot’s Rule Engine 2.0: A Structured Approach to IoT Automation

  • A Quiet Shift Is Coming to the Favoriot Platform

    Most IoT platforms start with a simple promise.Connect devices. Collect data. Show dashboards. That promise served the industry well for years. But something has been missing. As more devices come online and data volumes grow, static rules and fixed thresholds become limiting. Alerts trigger too late. Patterns remain hidden. Decisions… Read More ⇢

    A Quiet Shift Is Coming to the Favoriot Platform

  • Favoriot Sembang Santai Episode 12: The Favoriot Journey

    Episode 12 of Favoriot Sembang Santai is a special edition that takes listeners back to the very beginning of the Favoriot story. Hosted by Zura Huzali, this session features an in-depth conversation with Dr. Mazlan Abbas, one of the founders and the driving force behind Favoriot, as they reflect on… Read More ⇢

    Favoriot Sembang Santai Episode 12: The Favoriot Journey

  • Designing IoT Systems That Survive Intermittent Connectivity

    Most IoT slide decks assume one thing without saying it out loud.The network is always there. In reality, the network is often the weakest part of the system. I have seen IoT deployments in plantations, construction sites, ships, rural towns, and industrial yards where connectivity is best described as “comes… Read More ⇢

    Designing IoT Systems That Survive Intermittent Connectivity

  • From Lab to Market: Reflections on the IEEE Industry–Academia Forum on Energy Harvesting for IoT

    Yesterday (December 18, 2025) marked the closing session of the IEEE CAS Seasonal School for IoT Devices with an engaging Industry–Academia Forum titled “From Lab to Market: Commercialising Energy Harvesting Technologies for IoT Devices.” Held at the Banquet Hall, Kulliyyah of Engineering, IIUM, the forum brought together researchers, industry practitioners,… Read More ⇢

    From Lab to Market: Reflections on the IEEE Industry–Academia Forum on Energy Harvesting for IoT