Cloud computing has been a catalyst for accelerating the use of IoT among 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 have not been able to capture, process and analyze it. Now with communication technologies, such as Wifi, LTE and 5G, it is possible to take advantage of the opportunities provided by the data from the devices in process.

Cloud-based Enterprise Internet of Things (IoT) platforms are making it possible for organizations of any size to create applications that improve productivity and efficiency. In general, they operate on a pay-per-use model, making them easy to use for 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 or machine-to-machine (M2M) communication is the fundamental use case for IoT. By connecting two local or remote devices, organizations can achieve efficiency and avoid disruptions in production. The IoT platform organizes communication between devices according to predefined rules and business logic. A simple example of device-to-device communication is controlling HVAC based on room temperature reported by a thermostat and % occupancy. In industrial scenarios, equipment manufacturing in two production units is connected to the cloud-based IoT platform. When an outage is detected in one of the units, the equipment at the remote site is automatically turned on to maintain the expected production level.

Contemporary IoT platforms offer out-of-the-box M2M capabilities. They instantly bring value to connected devices by orchestrating the workflow between devices.

Centralized command and control

In this case the use is focused on connecting devices to the software. By allowing remote access to devices from applications, they can be controlled from anywhere. Desktop, web and mobile applications become remote on/off controls and even operating parameter modification controls.

>> a case study of this process is efficient control of boilers

Remote monitoring

Connected devices are capable of transmitting telemetry and status information of different process variables to the cloud. In this way, data in the cloud from remote devices enables continuous monitoring of device or process status. Even if devices are not remotely modifiable or controllable, status monitoring proves valuable to companies. By incorporating predefined rules to trigger actions, organizations can alert the appropriate teams when a device is not functioning properly or is out of 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 status of devices, historical data can be processed over a period of time to uncover 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 channeled into enterprise data warehouses to correlate with existing data. Translated with www.DeepL.com/Translator (free version)

Business Intelligence

Machine & Machine

Remote control and monitoring

Big Data