Executive summary Differential pressure (ΔP) measurement sits at the intersection of energy, IAQ, compliance, and reliability  in HVAC. It’s used for filter loading, duct static pressure, airflow inference, fan performance, and room pressurization (cleanrooms / isolation rooms). Three types of sensor dominate the market: Mechanical gauges : lowest cost and simplest deployment, but usually local-only  visibility unless you add switches or manual rounds. Wired electronic transm

IoT water quality sensors are reshaping how industries and municipalities monitor and protect water resources. By delivering real-time data on key parameters like pH, turbidity, temperature, and dissolved oxygen, these smart sensors enable early detection of contamination, improved regulatory compliance, and more informed decision-making. From agriculture to municipal water systems, advancements in accuracy, connectivity, and energy efficiency are making IoT-based water monit

Differential pressure is a simple signal with outsized value: it reveals clogging filters, airflow imbalance, duct leakage, fan performance drift, and containment failures before they become costly downtime. In this article, I break down the top 20 industrial monitoring applications for the Ellenex PDT2—spanning HVAC and IAQ, data centers, cleanrooms, process vessels, pipelines, and facility operations. If you’re building a predictive maintenance program or modernizing instru

100 LPWAN Solutions for Water and Wastewater Industry

Excerpt (for LinkedIn / article preview) Choosing between NB-IoT and Cat-M1 (LTE-M) in the US market isn’t a spec-sheet exercise—it’s a lifecycle business decision. The right choice affects battery replacement cycles, OTA firmware strategy, field maintenance costs, coverage risk by region, and whether your product can scale from a low-data pilot to a nationwide deployment. This article breaks down the technical differences that actually move ROI—mobility, payload headroom, la

California's water infrastructure is older than my grandpa! LPWAN solutions Enhance Infrastructure Performance, if designed properly, integrate to the legacy systems carefully and deployed in consideration of current and future requirements.

Ensure safety and regulatory compliance in medical, pharmaceutical, and aerospace sectors with LoRaWAN® and NB-IoT differential pressure monitoring. This technical guide examines how the Ellenex PDT2 series manages positive and negative pressure environments to prevent contamination and infection spread. Discover the advantages of LPWAN-based condition monitoring for HVAC filters, hospital isolation rooms, and ISO-rated cleanrooms, featuring high-precision data for audit-read

Choosing the right differential pressure sensor can significantly impact accuracy, efficiency, and long-term operating costs. This article compares the modern, wireless Ellenex PDT2 with the traditional Dwyer Magnehelic gauge, highlighting key differences in precision, data integration, installation, and scalability. While the Magnehelic remains a reliable mechanical option for simple visual monitoring, the PDT2 stands out with high accuracy, low-power operation, and seamless

Unlock the power of Cloud-Based Calibration Management for Industrial IoT. This guide explores how water utilities, mining, and smart cities are replacing costly field visits with remote, API-driven sensor adjustments. Learn how AI-driven drift detection, OTA offset scaling, and blockchain-backed traceability ensure peak data integrity for LPWAN devices. Reduce downtime, automate compliance, and scale your IIoT infrastructure with next-gen, future-proof calibration solutions.

A major healthcare facility was struggling to maintain safe airflow, negative-pressure performance, and filter efficiency across its HVAC system—while still keeping energy and maintenance costs under control. In this case study, Ellenex deployed its NB-IoT PDT2-N differential pressure sensor with built-in temperature monitoring and the Ellenex Software Platform to deliver near real-time visibility, remote access, and predictive analytics. The result: earlier detection of perf