other content about our technology & solutions
other content about our technology & solutions
IIoT Blueprint Part I:
Choosing the Right Solution
In this white paper, understand what to look for—and what to avoid—when selecting an IIoT solution. In this multi-part series, we outline how to navigate IIoT offeringsm, select the right applications, get IIoT off the ground, and scale that solution within your organization.
The Battery Barrier to Widespread Industrial Insights
In this Plant Services article, learn how, for facilities that wish to monitor thousands of assets, the cost of putting thousands of battery-powered devices on maintenance schedules is daunting.
STM Eversensor Installation
In this video, learn how to complete the simple, tool-less installation of the Steam Trap Monitor Eversensor — from start to finish in under 10 minutes!
Making Sense of Industrial IoT Platforms: The Battery Problem in IIoT Solutions
In 2012, IBM predicted 1 trillion connected devices by 2015. We didn’t get close to that number. In early 2017, Gartner forecast 50 billion devices by 2020, but even that prediction might be optimistic.
If it has such game-changing potential, why have businesses been slow to deploy IoT technology?
Emerging Industrial Internet Technology Can Reduce Costs and Dangers in Steam Systems
Steam systems are vital to the smooth operation of so many facilities. Yet, despite their critical function, the majority of plants rely on time- and labor-intensive manual inspections. With the emergence of industrial Internet technology, steam traps make ideal candidates for automated sensing technology.
In this video, learn more about the pervasive and costly problem of faulty steam traps and PsiKick’s novel monitoring solution using our patented batteryless sensing technology.
How to Reduce the Hidden Costs and Dangers Lurking Throughout Your Steam System
Read about the risks and costs inherent in every steam system and why two common “solutions” simply don’t solve the problem. Learn about an easy-to-deploy, cost-effective solution: Everactive’s continuous monitoring system that uses batteryless sensors to deliver real-time alerting through the cloud, without the need for manual inspection — ever.
The Battery Problem:
In this infographic, dive into the mind-boggling logistics of a battery-powered Internet of Things and learn how only self-powered, batteryless sensors can get us to a world of true ubiquitous computing.
Overcoming the Battery Obstacle to Ubiquitous Sensing — Finally: Why Self-Powered Sensors are the Game-Changer
Equipping objects with computing devices that lets them transmit data over the Internet has promised for years to revolutionize the way businesses operate and individuals live. If it has such game-changing potential, why have businesses been slower than anticipated to deploy IoT technology? One reason has been the fact that powering the IoT revolution could demand 25 billion, or 50 billion, or 1 trillion batteries. And that’s no small problem.
Everactive Technology Overview
In this video, learn about Everactive’s game-changing approach to wireless sensing with its completely batteryless and self-powered technology.
A Top-Down Approach to Building Batteryless Self-Powered Systems for the Internet-of-Things
This paper presents a top-down methodology for designing batteryless systems for the Internet-of-Things (IoT).
We start by extracting features from a target IoT application and the environment in which it will be deployed. We then present strategies to translate these features into design choices that optimize the system and improve its reliability. We look into how to use these features to build the digital sub-system by determining the blocks to implement, the digital architecture, the clock rate of the system, the memory capacity, and the low power states. We also review how these features impact the choice of energy harvesting power management units.
A 116nW Multi-Band Wake-Up Receiver with 31- bit Correlator and Interference Rejection
This paper presents a 116nW wake-up radio complete with crystal reference, interference compensation, and baseband processing, such that a selectable 31-bit code is required to toggle a wake-up signal.
The front-end operates over a broad frequency range, tuned by an off-chip bandselect filter and matching network, and is demonstrated in the 402-405MHz MICS band and the 915MHz and 2.4GHz ISM bands with sensitivities of -45.5dBm, -43.4dBm, and -43.2dBm, respectively. Additionally, the baseband processor implements automatic threshold feedback to detect the presence of interferers and dynamically adjust the receiver’s sensitivity, mitigating the jamming problem inherent to previous energy-detection wake-up radios. The wake-up radio has a raw OOK chip-rate of 12.5kbps, an active area of 0.35mm2 and operates using a 1.2V supply for the crystal reference and RF demodulation, and a 0.5V supply for subthreshold baseband processing.