Vibration Sensors for Industrial Internet of Things (IIOT)

  • Truly Wireless
  • Contains an accelerometer as well as temperature, pressure and humidity sensors.
  • Can be adhesive mounted, stud mounted or magnet mounted on rotating equipments
  • Sensor installations can be completed in less than 5 minutes
  • Meets stringent industry standards such as: ATEX Zone 0, ASME Class 1 Div 2, NEMA 250, UL746C, IP69K/IPX7, FCC & IC (Currently under testing, however, the preliminary product design is likely to pass qualifications as per leading standardization organization)
  • High performance MEMs based sensor upto +-25g acceleration range.
  • Rated for -450C to 1250C.
  • Rated up to 5kHz
  • Can measure +-2g, +-4g, +-8g, +-16g, +-24g
  • Ultra low power mode consumption down to 2µA
  • Vibration & Natural Frequency Testing passed
  • Unique Skeleton holder ensures noise down to 0.0001%
  • Upper gore vent ensures explosion proof design
  • Optimized embedded hardware and firmware programming ensures battery life of 1-3 years depending on (12 measurements/day to 4 measurements/day)

Wireless Vibration Sensor for both early and late stage defects

Catches faults such as:

  • Bearing Inner Race Failure
  • Bearing Outer Race Failure
  • Bearing Cage Failure
  • Bearing Roller Failure
  • Shaft Misalignment
  • Single Gear Tooth Failure
  • Multiple Gear Tooth Failure
  • Early Stage Shaft Cracking
  • Late Stage Shaft Cracking
  • Cavitation
  • Machine Imbalance
  • Patented for our combination of specialized signal and neural network processing methods. Our process ensures the lowest error rate, fastest convergence rate and catches faults with greater than 99% accuracy.
  • Specialized neural networks algorithm used for autocalibration of sensors giving highly consistent and noise free readings
  • Multi sensor fusion using Deep Learning with specialized neural networks that provides absolutely low error rate of the order of 1e-20.
  • Gathers up to 145 features (best in class for vibration analysis software) enabling highly accurate fault diagnosis and determination of remaining useful life.

Machine Learning based health updates

  • Combination of specialized neural networks & kernel based extrapolation methods used for predicting remaining useful life with more than 90% accuracy.
  • Gathers all kinds of time domain, frequency domain and time frequency domain features
  • Specialized neural networks algorithm used for autocalibration of sensors giving highly consistent and noise free readings

Secure data transmission to Cloud server

  • Complies with TLS 1.2 Security Protocol
  • Data traffic originates from sensor, no connection from server
  • Completely server-less architecture
  • Sensor data is stored locally with scheduled uploads to the cloud using the most highly-secure platform in the world (certified by UL).
  • Complete data pipeline is encrypted

Real-time alerts and reports

  • Week incipient fault alerts
  • Characteristic fault alerts (such as Bearing Inner Race Failure)
  • Text & Email alert system available
  • Low battery alert available

User-friendly dashboard available on mobile devices

  • Approved users stay updated on the health of their equipment from anywhere at any time.
  • Data can be accessed for independent analysis.
  • Data, images, drawings can be tied to individual sensors to provide technicians with information on the location of the equipment and sensors as well as other user-defined information such as P&ID’s etc.
  • Vibration data by axis, Vrms vs. Time, Kurtosis vs. Time, Machine Life and Machine Health etc available at a glance


Install VibrationLF

Wireless sensors mounted at the optimal location on your equipment using Nanoprecise’s patented platform. (app? System?)


On the cloud, data is processed in real time using sophisticated signal processing methods


Patented and state of the art deep learning algorithms learn from the processed data and estimate the following:
- Remaining time to reach the specific mode of failure (Prognosis)
- Once the failure has been detected, the software identifies the mode of failure.


The health condition of various components of each piece of equipment is available in real-time on your smart-phone, tablet or desktop.