Uploaded February 2023 | Updated September 2026, 1 week ago
Learn how to leverage cellular IoT technology and embedded machine learning to develop predictive maintenance applications.
In this webinar, you will learn how to reduce costs and downtime by predicting failures and scheduling maintenance before a breakdown occurs. We will also investigate the different Low Power Wide Area Network technologies currently available, the current landscape of cellular IoT, coverage, rollout, and the future of this technology. There is also essential to distinguish between low-power cellular IoT and Cat 1 bis, and what these technologies are designed to solve.
0:00 Practicalities and agenda
2:25 Introduction
2:40 Current LPWAN Landscape
5:20 LTE-M and NB-IoT Coverage Map
6:15 LTE IoT Technologies overview
8:57 Are Cat 1 bis suitable for massive IoT deployments?
12:00 Cellular evolution 2G to 5G
13:29 LTE categories evolution
14:14 What will happen with 2G/3G/4G
15:53 Different types of maintenance
18:14 Predictive maintenance overview
19:34 Where would it make sense to use predictive maintenance?
21:45 Why use cellular IoT for predictive maintenance?
23:11 Process data on the cloud or device side?
25:30 What to consider when implementing ML
28:19 Benefits of using ML in predictive maintenance
29:07 Cellular radio power consumption
30:58 Break-even comparison - LTE vs. CPU
32:24 The advantages of nRF9160 SiP
34:50 Q&A
This is a recording of a webinar held on February 8, 2023.
The presentation can be downloaded here (direct download): devzone.nordicsemi.com/cfs-file/__key/communityserver-discussions-components-files/4/Using-Cellular-IoT-for-Predictive-Maintenance.pdf
#cellularIoT #machinelearning
Learn how to leverage cellular IoT technology and embedded machine learning to develop predictive maintenance applications.
In this webinar, you will learn how to reduce costs and downtime by predicting failures and scheduling maintenance before a breakdown occurs. We will also investigate the different Low Power Wide Area Network technologies currently available, the current landscape of cellular IoT, coverage, rollout, and the future of this technology. There is also essential to distinguish between low-power cellular IoT and Cat 1 bis, and what these technologies are designed to solve.
0:00 Practicalities and agenda
2:25 Introduction
2:40 Current LPWAN Landscape
5:20 LTE-M and NB-IoT Coverage Map
6:15 LTE IoT Technologies overview
8:57 Are Cat 1 bis suitable for massive IoT deployments?
12:00 Cellular evolution 2G to 5G
13:29 LTE categories evolution
14:14 What will happen with 2G/3G/4G
15:53 Different types of maintenance
18:14 Predictive maintenance overview
19:34 Where would it make sense to use predictive maintenance?
21:45 Why use cellular IoT for predictive maintenance?
23:11 Process data on the cloud or device side?
25:30 What to consider when implementing ML
28:19 Benefits of using ML in predictive maintenance
29:07 Cellular radio power consumption
30:58 Break-even comparison - LTE vs. CPU
32:24 The advantages of nRF9160 SiP
34:50 Q&A
This is a recording of a webinar held on February 8, 2023.
The presentation can be downloaded here (direct download): devzone.nordicsemi.com/cfs-file/__key/communityserver-discussions-components-files/4/Using-Cellular-IoT-for-Predictive-Maintenance.pdf
#cellularIoT #machinelearning
