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Editor's Pick (1 - 4 of 8)
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IoT: Enabling the Safer, Connected Warehouse

Steve Walker, CIO & COO, DHL Supply Chain Asia Pacific

IOT-Turning out to be a phase of evolution

Mayank Bhargava, CIO, DHFL Pramerica Life Insurance

Connecting dots the IoT way!

Sunil Singh, Regional Chief Information Officer, Coca-Cola Beverages Vietnam

Industrial Scientific Blazes a Trail in IoT

David DiLeo, CIO, Industrial Scientific Corporation

How Internet of Things (IoT) will Rewire Supply Chains

Chad Lindbloom, CIO, C.H. Robinson

What's The CIO Got To Do With The IoT?

Sharon Gietl, VP of Information Technology and CIO, The Doe Run Company

The Internet of Things, in the Real World

Manuel Bautista, CIO, Harvard Maintenance

IoT Platforms: What are they and do you need one?

Tekin Gülşen, CIO, IT Director, Brisa Bridgestone Sabancı

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IoT and its Implementation

CIOAdvisor Apac | Friday, April 05, 2019
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Internet of ThingsIoT (Internet of Things) involves different technologies, devices, and processes. Together they are transforming enterprises operations, enable automation, and deliver valuable insights. But to implement an IoT project successfully in any sector few factors needed to be considered, following are some of them:

IoT device management: IoT relies on physical sensors and devices like cameras, sensors, and motion detectors that are placed in equipment or space to collect data. Enterprise should deploy IoT technology to recognize the problem and solve. They should acquire suitable devices to perform the tasks. The devices should be fully functional and updated with appropriate firmware and required security settings to achieve a continuous feed of data.

Edge devices: Devices should be connected to a common network to communicate with each other. Collected data is processed in real time using edge computing tools. The tools allow the collected data to be processed, scrubbed and formatted at the point of origin before sending over to the central console or the cloud server for analysis.

Check Out CIOAdvisor's TOP IoT Solution Providers -  LX Group, PTC [NASDAQ: PTC], RenGlobe Tech Solutions,...

Cold and hot path analysis: To fully capitalize on the data generated by IoT devices, Artificial Intelligence, and machine learning are utilized to analyze data that has been collected and stored for an extended period, known as cold path data. Hot path data analytics is the process of real-time data from the sensors. Machine learning algorithms can be integrated into an edge device to enhance decision-making processes. The hot path analysis is deployed using complex event processing technology (CEP) after the initial data pattern is established using cold path analytics.

Data storage: The data is moved between the systems, and into the cold path analytics for additional processing, or retrieved for reporting.  Enterprises venturing into IoT projects should consider their business goals and objectives to identify the amount of data required for an adequate analysis

System integration: Companies should consider the different dimensions and layers of technology.

The data is relayed to dashboards to visualize the insights, system status, and impending maintenance.

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