Monitron is an end-to-end monitoring service based on machine learning (ML) that makes it possible to detect industrial machine-related issues at an early stage before they become catastrophic failures. It includes IoT Monitron Sensors, IoT Monitron Gateway, Monitron Service and Monitron App.
Let me explain what all of these components are and how they work.
IoT Monitron Sensors(1) are Bluetooth devices that can be attached to equipment such as gearboxes, pumps in order to capture the temperature and vibrations and send them to the Monitron Gateway(2) via Bluetooth. Sensors are wireless with estimated 3-year battery life and are updated over the air (OTA) providing system improvement over the life of your installation. OTA refers to any type of wireless transmission.
IoT Monitron Gateway(2) is a physical device that can be connected via wifi to the local Internet and you can charge by plugging in the power cable. The purpose of this device is to collect the data from sensors and transfer sensor data to the cloud. Up to 20 sensors can be connected to a single gateway which can be located up to 30m away.
You can sign in to AWS console management and find the service called “Amazon Monitron”(3) which is based on machine learning, there is no required machine learning knowledge to use this service. This service analyzes the data sent by the AWS Gateway (2), and implements predictive analytics based on these data. But what kind of prediction are we talking about? This service can detect issues in equipment patterns and deliver results. So easy to set up, you can create a project and give this project permission to a user to manage it. Then you can download and install the application on your device.
Monitron App(4) is used for maintenance technicians to monitor equipment behavior in real-time. You can log in to this application using the same credentials that are set up in step three. Once you are logged into the application you can set up the Monitron Gateway(2). Then the gateway is added on the mobile device via Near Field Communication (NFC). A technical engineer through the mobile app can identify whether the equipment is healthy or unhealthy. Then, a technical engineer can go and do some inspections where unhealthy equipment is set up.
Why Smart Sensors?
Hardware is becoming smaller and getting cheaper giving you the information you need. Making IoT devices widely available for a variety of applications ranging from predictive maintenance to user behavior monitoring.
Use Case
These sensors can be used in almost any IoT environment, from manufacturing to home appliances. In manufacturing and home appliances, these sensors can continually measure the temperature and vibration of the machine to ensure it stays within a secure threshold. It can also be used in agriculture to capture the temperature of the soil, water, and plants. These IoT devices are produced by AWS and can’t be integrated with third-party tools sensors. In case you have your own sensors, I will recommend you to use Amazon Lookout for Equipment that supports customer sensors.
AWS Panorama Appliance is a smart device based on machine learning. This service makes predictions based on the images captured by cameras that are added to this appliance.
How does it work?
There are three main components that work together:
Amazon Panorama Device Appliance(1): This device is produced by AWS and allows you to build a custom computer vision application. This device will be connected to the camera stream(2) on your local network and registered to the AWS panorama service(3) in the cloud.
On-Premise Cameras(2): First of all, not all types of cameras can be adaptable for this appliance, except H.264 for live streaming which is supported and it supports up to 10 cameras simultaneously. The cameras are connected via wifi or ethernet to the appliance and they send all the data in real-time to the appliance.
Amazon Panorama Service(3): This service allows you to set up an appliance configuration. When you start to set up an appliance, this service gives you the file configuration that you need to transfer to the appliance to connect with AWS. You can download these files and transfer them to an appliance via USB drive. AWS Panorama uses IoT Greengrass to manage the AWS Panorama Appliance, store data, and import application resources. Once the appliance is connected to the local network it will start to communicate with AWS Internet of Think (IoT) Greengrass.
Over the past decade, we have seen exponential growth in video analytics applications and will continue over the next few decades across all businesses and industries. Videos can be used to identify objects, people, cars, both in appearance and in movement. This data can help organizations make better decisions through analytics without having the necessity of human inspection. Videos can be used in many business areas such as government, healthcare, transportation (traffic monitoring), event management (conferences, films, shows, museums, concerts), retail operations, security and surveillance.
All these smart industrial equipment are very useful in the industrial world today, helping customers to automate all processes and reduce costs. They are simple cost-effective solutions leveraging machine learning capabilities to make predictions in real-time.
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