57 posts tagged with "Industrial IoT"

Every second, a modern manufacturing plant generates millions of data points. PLC registers cycle through readings, sensors capture temperatures and pressures, vision systems inspect parts, and motor drives report speed and torque values. The question isn't whether to collect this data — it's where to process it.

For the past decade, the default answer was "send everything to the cloud." But manufacturers are learning the hard way that shipping every data point from every machine to a cloud server creates problems: network bandwidth costs, latency that prevents real-time action, dependency on internet connectivity, and enormous cloud compute bills.

Edge computing — processing data at or near the source — is emerging as the practical answer for most manufacturing IIoT applications. Here's why it matters, how it works, and what to consider for your factory.

MachineMetrics has built a strong reputation in the CNC machine monitoring space, delivering real-time OEE tracking and production visibility for discrete manufacturers. MachineCDN takes a broader approach, providing AI-powered predictive maintenance across all types of manufacturing equipment — from CNC machines and injection molders to compressors, pumps, conveyors, and HVAC systems. This comparison helps manufacturers understand when CNC-specific monitoring is enough and when you need a full-factory predictive maintenance platform.

Samsara and MachineCDN both appear in IIoT platform evaluations, but they serve fundamentally different markets. Samsara built its business on fleet management — GPS tracking, driver safety cameras, and vehicle telematics — and has been expanding into facility and equipment monitoring. MachineCDN was purpose-built for manufacturing, delivering AI-powered predictive maintenance with plug-and-play hardware and cellular connectivity. This comparison helps manufacturers understand where each platform excels and which one actually solves manufacturing problems.

Litmus has established itself as a recognized edge computing platform for industrial environments, earning a Gartner Challenger position in the IIoT Platforms category. But Litmus isn't the right fit for every manufacturer. Whether you're concerned about deployment complexity, total cost of ownership, the lack of built-in analytics, or simply want to evaluate options before committing, this guide covers the best Litmus alternatives for 2026 — evaluated through the lens of what matters most to manufacturing operations teams.

If you've been evaluating Litmus for your IIoT deployment, you've probably noticed something: there's no pricing page on litmus.io. That's intentional. Like most enterprise IIoT platforms, Litmus uses custom pricing that varies based on deployment size, features, and negotiation leverage. This guide provides the most comprehensive breakdown of Litmus pricing available in 2026, based on publicly available information, industry benchmarking, and feedback from manufacturing teams who have gone through the Litmus procurement process.

The Industrial IoT platform market is projected to reach $33.3 billion by 2027, according to MarketsandMarkets research. But for manufacturing leaders evaluating platforms in 2026, the sheer number of options creates more confusion than clarity. Gartner's Magic Quadrant, Forrester Wave reports, and vendor marketing all tell different stories. This guide cuts through the noise with a practitioner-focused ranking of the best IIoT platforms in 2026, evaluated on the criteria that actually matter on the factory floor.

Choosing an Industrial IoT (IIoT) platform is one of the most consequential technology decisions a manufacturing leader can make. Get it right, and you unlock predictive maintenance, real-time visibility, and measurable ROI within weeks. Get it wrong, and you're looking at months of integration work, six-figure professional services bills, and a pilot that never scales. In this head-to-head comparison, we break down MachineCDN vs Litmus across every dimension that matters to plant managers and operations engineers.