Explore the potential of cellular IoT technology and embedded machine learning for developing predictive maintenance applications in this 47-minute webinar. Discover how to reduce costs and downtime by predicting failures and scheduling maintenance proactively. Gain insights into various Low Power Wide Area Network technologies, the current cellular IoT landscape, coverage, rollout, and future prospects. Understand the distinctions between low-power cellular IoT and Cat 1 bis, and their specific applications. The webinar covers topics such as the LPWAN landscape, LTE-M and NB-IoT coverage, cellular evolution from 2G to 5G, types of maintenance, benefits of predictive maintenance, considerations for implementing machine learning, and power consumption comparisons. Includes a Q&A session and offers access to downloadable presentation materials.
Overview
Syllabus
Practicalities and agenda
Introduction
Current LPWAN LandscapeÂ
LTE-M and NB-IoT Coverage MapÂ
 LTE IoT Technologies overviewÂ
Are Cat 1 bis suitable for massive IoT deployments?Â
Cellular evolution 2G to 5GÂ
LTE categories evolutionÂ
What will happen with 2G/3G/4GÂ
Different types of maintenance
Predictive maintenance overviewÂ
Where would it make sense to use predictive maintenance?Â
Why use cellular IoT for predictive maintenance?Â
Process data on the cloud or device side?Â
What to consider when implementing MLÂ
Benefits of using ML in predictive maintenanceÂ
Cellular radio power consumptionÂ
Break-even comparison - LTE vs. CPUÂ
The advantages of nRF9160 SiPÂ
Q&A
Taught by
Nordic Semiconductor
Related Courses
-
The Power of Cellular IoT in LPWAN Applications
-
NRF9160 - Optimized for Ultra Low Power and Small Cellular IoT Applications
-
Navigating the Design Complexities of Low Power LTE-M and NB-IoT Networks
-
Five Essential Building Blocks for Cellular IoT Development With A1 Digital
-
Expand Cellular IoT Coverage with iBASIS IoT Connectivity
-
Low Power Cellular for the IoT
