How to implement successful IoT projects
ONE technology that is expected to have a significant impact on industries and enterprises in the near future is the internet of things (IoT).
IoT is not a single technology but a network of different technologies, devices, and processes that are expected to transform enterprise operations, enable automation, and deliver valuable insights at the same time.
However, to successfully implement an IoT project in any given industry, several factors need to be considered.
# 1 | IoT device management
IoT technology relies on physical sensors and devices such as cameras, acoustic sensors, and motion detectors that are placed in equipment or space to gather data.
It is crucial that the enterprise deploying the IoT technology recognizes the problem it is seeking solutions for and acquires suitable devices to perform the tasks.
These devices have to be fully functional and updated with appropriate firmware and required security settings so that a continuous feed of data is possible.
# 2 | Edge devices
Devices then must be connected to a common network to be able to communicate with each other. Data gathered is initially processed in real time using edge computing tools.
Using edge computing systems allows for the data collected to be processed, scrubbed, and formatted at the point of origin before being sent over to the central console or the cloud server for analysis.
# 3 | Cold and hot path analytics
To fully capitalize on the data generated by IoT devices, advanced systems such as AI and machine learning could be deployed to analyze data that has been collected and stored for an extended period, otherwise known as cold path data.
Hot path data analytics meanwhile is the processing of the real-time data from the sensors, whereby machine learning algorithms can be integrated into an edge device, enabling an instantaneous business decision.
This hot path analysis is often deployed using complex event processing technology (CEP), after initial data pattern is established using the cold path analytics.
# 4 | Data storage
When the data is transmitted to the IoT system by the sensors, it is stored long term to allow for analysis.
The data could be moved between the systems, into the cold path analytics for additional processing, or retrieved for reporting. Depending on the network, the size of storage could swell up from terabytes to exabytes.
Enterprises venturing into IoT projects should carefully consider their business goals and objectives to identify the amount of data required for adequate analysis that delivers on their goals.
# 5 | System integration and dashboard
IoT does not usually exist as a standalone system but instead connected to other systems or a platform to allow for insights to be funneled into other applications or management systems.
The data would also generally be relayed to dashboards that visualize the insights, system status, impending maintenance, and other measurables.
So, companies seeking to successfully adopt IoT technology must consider the different dimensions and layers of the tech carefully.