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. 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. 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 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. 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 fundamental use case for 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-art M2M capabilities. They instantly add value to connected devices by organizing workflow across devices. Instantly add value to connected devices by organizing 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 apps, they can be controlled from anywhere. Desktop, web and mobile applications become remote on/off controls and even controls for modifying operating parameters.
>> a case study of this process is efficient control of boilers
Remote monitoring with the use of IoT
The connected devices are capable of transmitting telemetry and status information of the 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
Control and command
Remote monitoring
Machine & Machine
Remote control and monitoring
Big Data
Device 1
Device 2
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