Business

By Marc Kavinsky, Lead Editor at IoT Business News. MultiTech has introduced a Tridium Niagara driver designed to let building teams add and manage LoRaWAN sensors from inside the Niagara Framework, aiming to reduce the integration work typically required to connect IoT telemetry to BMS applications. Smart building projects routinely stall on an unglamorous problem: […]

Industrial systems are entering a new phase where data, connectivity, and automation converge at scale. The concept of Smart Manufacturing sits at the intersection of these forces, reshaping how factories operate, how assets are managed, and how decisions are made across production environments. For IoT decision makers and industrial leaders, Smart Manufacturing is not a

Asset Tracking has become a foundational capability within the Internet of Things (IoT) ecosystem, enabling organizations to monitor the location, condition, and movement of physical assets in near real time. From industrial equipment and shipping containers to medical devices and returnable transport items, the ability to maintain continuous visibility across distributed environments is increasingly seen

The Internet of Things (IoT) has already transformed how devices communicate, how businesses operate, and how individuals interact with technology. Yet what we’ve seen so far is only the foundation. By 2030, IoT will no longer be defined simply by “connected devices.” Instead, it will represent intelligent, self-optimizing systems that operate with minimal human intervention.

Industrial IoT has become a central component of modern industrial systems, driven by the need to improve operational efficiency, resilience and visibility across increasingly complex environments. As industrial assets generate growing volumes of data, organizations are looking beyond basic connectivity to extract meaningful insights that can support real-time decision-making and long-term optimization. At its core,

By Marc Kavinsky, Lead Editor at IoT Business News. Berg Insight forecasts the active installed base of video telematics systems in North America and Europe to reach about 22 million units by 2030, underscoring how quickly camera-led safety and operations tools are becoming mainstream in commercial fleets. Fleet telematics has long been about location, engine

Edge AI is emerging as a critical enabler for next-generation IoT systems, allowing data processing and decision-making to occur closer to where data is generated. As connected devices proliferate across industries, the limitations of centralized cloud processing—particularly in terms of latency, bandwidth, and privacy—are becoming increasingly evident. By integrating artificial intelligence directly into edge devices

By Marc Kavinsky, Lead Editor at IoT Business News. Wiliot has partnered with Databricks to run its Physical AI platform and supply chain automation solutions on the Databricks platform, aiming to make large volumes of item-level sensor data easier for enterprises to ingest, govern, and use for operational decisions. For all the talk about AI

Managing connected devices at scale has become one of the most complex challenges in the Internet of Things ecosystem. As deployments move from pilot projects to thousands or millions of endpoints, organizations must ensure that devices are securely provisioned, continuously monitored, and efficiently maintained throughout their operational life. This is where IoT Device Management plays

Industrial websites are no longer static marketing assets. They are becoming operational systems that support product delivery, data exchange, and business processes across industrial organizations. As manufacturing, logistics, and engineering companies digitize their workflows, the website shifts from a presentation layer into a functional layer that connects products, users, and systems. This shift reflects a