Cloud computing has been a catalyst to accelerate 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 the devices were able to generate telemetry data, companies had not been able to capture, process, or analyze it. Now with the evolution of communication technologies such as LTE and 5G, it allows you to take advantage of the ideas that applications provide with the data provided by devices in process.

Cloud-based Enterprise Internet of Things (IoT) platforms are enabling organizations of any size to build connected applications that improve productivity and efficiency. In general, they operate under a pay-as-you-go model, making it easier 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 critical use case of IoT. 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. 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-box M2M capabilities. Instantly add value to connected devices by organizing workflow between 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 remotes and even operating parameter modification controls.

>> un caso práctico de este procesos es el control eficiente de las calderas

Remote monitoring

Connected devices are able to transmit telemetry and status information of different process variables to the cloud. In this way, data from remote devices in a centralized repository can continuously allow monitoring of device or process status. Even if devices are not remotely modifiable or 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 device health, 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 business data stores to correlate with existing data.

Business Intelligence

Machine & Machine

Remote control and monitoring

Big Data