Cloud computing has been a catalyst for accelerating the use of IoT across enterprises. The cloud made it possible to connect devices (sensors or machines) to traditional line-of-business applications such as ERP and asset tracking platforms.
Although devices have been able to generate telemetry data, companies had not been able to capture, process, or analyze telemetry data. Now with communication technologies such as LTE and 5G, you can take advantage of the opportunities provided by data from in-process devices.
Cloud-based Enterprise Internet of Things (IoT) platforms are making it possible for organizations of any size to build applications that improve productivity and efficiency. In general, they work under a pay-as-you-go model, making it easy to use in many customers.
As companies begin to evaluate solutions and use IoT in different enterprise applications, here are four scenarios that help them drive their connected device strategy.
Device-to-device communication
Device-to-device communication or machine-to-machine (M2M) communication is the case for critical IoT use. By connecting two local or remote devices, organizations can achieve efficiency and avoid production disruptions. The IoT platform organizes communication between devices according to predefined rules and business logic. A simple example of device-to-device communication is to control the HVAC based on the ambient temperature reported by a thermostat and the % occupancy. In industrial scenarios, the manufacture of equipment in two production units is connected to the cloud-based IoT platform. When an outage is detected on one of the drives, the computer at the remote site automatically turns on to maintain the expected production level.
Contemporary IoT platforms offer out-of-the-art M2M capabilities. They instantly add value to connected devices by organizing workflow across devices.
Centralized command and control
In this case the use focuses on connecting devices to the software. By allowing remote access to devices from apps, they can be controlled from anywhere. Desktop, web, and mobile applications become on/off remote controls and even operating parameter modification controls.
>> a case study of this process is efficient control of boilers
Remote monitoring
Connected devices are able to transmit telemetry and status information from different process variables to the cloud. In this way, data in the cloud of remote devices allows continuous monitoring of the status of the device or process. Even if devices are not modifiable or remotely controllable, health monitoring proves valuable to businesses. By incorporating predefined rules to trigger actions, organizations can alert the appropriate computers when a device is not working properly or exits some control parameter.
Business intelligence in the use of IoT
By ceding the alarm or action rule set to an intelligent machine learning algorithm that can learn from historical data for predictive device maintenance.
Telemetry data can be used to improve operational efficiency, production efficiency, and resource optimization. While real-time data is used to monitor the health of devices, historical data can be processed over a period of time to discover useful information. For example, telemetry ingested by connected vehicles can be collected, aggregated, processed, and analyzed for driving patterns, fuel efficiency, route optimization, and fleet management. Historical data can be piped to enterprise data stores to correlate with existing data.
Business Intelligence
Control and command
Remote monitoring
Machine & Machine
Remote control and monitoring
Big Data
Device 1
Device 2
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