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Getting Started With loT

[IMAGE: GETTY IMAGES]

The Internet of Things is a global system of interconnected physical devices that deliver data via the Internet, and the IoT is transforming the way we live and work. IoT devices have been widely adopted across a range of industries, including healthcare, manufacturing, automotive, retail, and building automation, just to name a few. Businesses are leveraging data from connected devices to increase operational efficiency and to provide improved value and experiences to their clients. With the pace of IoT adoption rapidly increasing, and with the number of connected devices already in the billions, the demand for skilled developers who are able to deliver IoT solutions continues to rise.

 

Hardware

Internet of Things devices can be simple, tiny devices on a telephone pole or complex remote computers or sensors located in adverse climates. The range of requirements is vast and the hardware engineering challenges mirror the uniqueness of these devices which subsequently push the limits of hardware design and implementation.

 

Security

Internet of Things is already suffering from several DDOS attacks, botnet. Security cannot be an afterthought for IoT devices.  Therefore, security is one of the biggest concerns in IoT.  Security must be built-in at every step of the design of the system, not added as an afterthought.  Critical issues that are closely related to security include data ethics, privacy and liability.

 

Networking

A large number of ways to send and collect data are created with all of the embedded sensors utilized in Internet of Things objects that communicate to one another. A reliable and secure avenue of traffic is vital, therefore electrical and network engineering skills will be essentials for the IoT. Existing, open and standard networking technologies imbedded in IoT devices/infrastructures is the goal and will drive the skills requirements.

 

 Machine Learning

Gathering and analysing a large amount of data would only make sense if we are able to decipher the pattern and eventually predict the outcome. As Internet of Things becomes more complex and ubiquitous, AI will be called upon to handle more tasks and make autonomous decisions. Intelligent big data analytics involves applying cognitive computing techniques drawn from data mining, modelling, statistics, machine learning, and AI. These techniques can be applied in real-time to sensor data streams for predictive analysis or to autonomously make decisions in response to incoming data and can also be applied to historical data to identify patterns or anomalies in the data.

 

Business Intelligence

As the number of IoT devices transmitting data increases, big data turns into really Big Data.  Developers will need big time data management skills to securely and reliably ingest, store, and query the vast quantities of heterogeneous data originating from these devices. Many IoT devices generate latency or time-sensitive data, so it is necessary to filter or discard irrelevant data. Key technologies and platforms for data analytics that IoT developers should develop skills in include Hadoop, Spark, and NoSQL databases like MongoDB.

 

UI / UX Design

Internet of Things objects will come in all shapes and sizes and User Interface and User Experience professionals will be needed to create interfaces that are effective and user-friendly.

Web and mobile applications are developed using high-level languages, with Java, Swift, and Node.js among the top languages for IoT app development. GPS programming skills are in particular demand, as many IoT applications, including wearables and smart vehicles, are location-aware.