LoRaWAN and LTE Cellular (CAT-M1 & NB-IOT)

Cellular IoT is all about connecting physical devices, such as sensors, to the internet using the same technology as your smartphone. These physical devices piggyback on the same mobile networks as smartphones, eliminating the need to create a new, private network to house IoT devices.

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Quick Introduction

What is LoRaWAN?

LoRaWAN stands for Long Range Wide Area Network and is used for connecting devices to the internet at long range (range of kilometers) and low power consumption (battery lasting Five or more years). The LoRa Alliance defines the LoRaWAN network architecture as a Cloud-based, low-power, wide-area (LPWA) network protocol. It is a popular specification for the Internet of Things (IoT). Users have the choice to connect their devices to the cloud using either a Private or a Public
network. While in the Private network, the users deploy their own LoRaWAN Gateway and deploy sensors in the range of those gateways, in the Public networks, the users pay a network operator to connect its sensors without having to deploy their gateways.

What is Cellular IoT?

Traditional cellular options such as 4G and LTE networks consume too much power to address the low-power requirements of battery-operated devices in the IoT space. For this reason, the 3GPP group worked on specifications to define a low-power solution to target IoT Use Cases. The results were the CAT-M1 and NB-IOT, LTE-based cellular technologies considered LPWAN suitable for low-power IoT devices. Although this technology consumes more power than LoRaWAN, it’s a good connectivity solution for areas with no LoRaWAN Public network available or a Private network gateway is not convenient. The ubiquity of cellular networks makes these technologies a good candidate for IoT Use Cases.

Cloud: AWS & Azure

Amazon Web Services, also known as AWS, is an amazing cloud platform that also turns out to be public. AWS is a scalable platform that supports and helps mobile and web applications run smoothly. Whereas, Microsoft Azure provides a Machine Learning Studio, a web-based and low-code environment, to configure machine learning operations and pipelines quickly