OEM Solutions

Edge Asset Monitoring and Management - HPE Edgeline and AT&T IoT Services

New technologies like Asset Management & Tracking Intelligence involve state-of-the-art technologies that aid smarter decision-making, while reshaping infrastructure strategies ensuring protection for company assets.

The assets are stored in a small refrigerator simulating a cold chain. Several environmental sensors monitor different types of assets. One method is RFID (radio-frequency identification) where assets individually tagged with RFID sensors, each with a unique pre-programmed ID. As these assets remove, a small RFID tag reader determines the assets’ absence or presence in the refrigerator, to help closely track inventory.

 To complement the tracking of the assets, temperature and humidity are monitored to maintain the expected lifespan of sensitive substances. Additionally, the power consumption of the refrigerator is monitored to determine any anomalies in power usage over time, helping to maintain the cold chain or simply to alarm upon a power loss. A door-open sensor is also connected to indicate the state of the door. A set of colored LED lights lines the door and can be controlled to provide simple visual feedback to any person near the refrigerator. 


Building Blocks of This Solution

The information about the assets and their environment is collected using sensors connected to the EL20 using various input capabilities: USB, DIO (digital I/O), and Wi-Fi. Software on the EL20 utilizes Docker containers in an Ubuntu environment. AT&T Flow Edge runs in the Docker container to periodically read data from the sensors and upload it to AT&T M2X IoT cloud service using the AT&T LTE network. A web-based portal is provided to display the information, allowing access to the information from anywhere with internet access. 

 Several sensors using various technologies and connection methods are used to collect information about the assets and their environment. Sensors connected by USB include an RFID reader and tags, a scale, thermometer/hygrometer, and controllable colored LED lights. Additional sensors include a smart power strip connected by Wi-Fi and a door open switch connected to digital I/O. 


HPE Edgeline EL20 Collects Data

The HPE Edgeline EL20 IoT System is a ruggedized, performance-optimized solution designed for data aggregation and compute. Designed for an industrial environment with a wide temperature range, shock, and vibration, and various input types, it is well-suited for this solution. 


AT&T Flow Edge 

AT&T Flow is an IoT application development and runtime environment. Based on Node-RED, AT&T Flow offers nodes that are pre-configured to allow easy access to multiple data sources, cloud services, device profiles, and communication methods. AT&T Flow Designer is a robust web-based development environment where data-driven applications are designed and deployed with ease. AT&T Flow Edge allows those applications to run on a device at the edge of the network instead of the cloud, to speed up decision making and reduce latencies. 

 The temperature and humidity sensors trigger every 20 minutes and send a command to the serial port data handler to read the temperature and humidity values and send those values to the AT&T cloud. The RFID reader triggers every 30 seconds to read the list of RFID tags that are inside the refrigerator. After reading the list, the data is parsed to extract the RFID tag values, then formatted and written to the M2X cloud. The power triggers every 30 seconds to read the latest power value (in Watts). This value does not need parsing, so it is formatted and then sent to the M2X cloud. 


Web Portal Presents The Cloud Data In Readable Format 

The web-based portal uses various graphical elements to display information from the M2X cloud. The information includes general data about the device such as manufacturer, model, and capacity data.


To summarise, this solution shows how the Edgeline Systems can collect data from a variety of devices using a wide range of communications technology, then process that data locally, and finally pass the results on to AT&T’s M2X cloud services. It leverages AT&T’s Flow Designer to simplify the process of designing and implementing the data flow, processing and actions. 


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