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Iot in the Emerging IT Landscape: Trends and Transformation

Iot in the Emerging IT Landscape: Trends and Transformation
October 06, 2017

Understanding IoT

Mark Zuckerberg‘s smart home, assisted by robot-styled Jarvis, is substantially saving time taken to complete domestic chores. It is developed in Python with conceptual influences from techniques of artificial intelligence (AI) and Internet of Things (IoT). IoT comes into the picture through home device connectivity, viz. interconnected televisions, washing machines, electrical switches, fans, gates, CCTV cameras, and so on. The devices are not only connected, but they communicate with each other as well.

A safety alert pops up in a car immediately after an adjacent car meets with an accident. Self-driving cars replace human capital through a collaboration of technologies such as machine learning, robotics-AI, IoT, networking, digitalization, caching, and sensors. As reliance on technology increases, the probability of errors, outages, and technical failures also rises in self-driving vehicles. Therefore, it is essential to operationalize accurate, efficient, error-proof mechanisms in the application of IoT.

Today, Amazon delivers goods to customers via drones by establishing communication lines between customers and drone devices. IoT finds applicability even in a pair of jogging shoes by providing metrics of distance covered, running speed, calories burnt, and body temperature on a single mobile screen.

The total data used worldwide last year was estimated at 16.1 zettabytes. By 2025, that will rise to 163 zettabytes, with most of the growth, and 20 per cent of the total, coming from IoT.

Learning IoT

IoT is poised to become a game changer in this era, marked by innovation and technological advancement.

It is important to start thinking, developing, deploying, and managing IoT before your enterprise runs out of memory, space, resources, and becomes outdated. So, developing your own IoT platform and deploying your projects in alignment is essential for exponential performance results.

There are numerous open sources having nearly 51 IoT project tools available.  

IoTivity is used for device-to-device communication. It is operable on Linux, Arduino, and Tizen.

Device Hive is a machine-to-machine communication framework for smart energy, home automation, telemetry, remote control, and software monitoring.

HCL has developed frameworks in alignment with the standards in the Eclipse Foundation development tool. It can be used and tested in a sandbox for testing project applicability.

We have developed other tools and frameworks, such as Node-RED based on node.js, M2Mlabs Mainspring based on Java, Apache Cassandra NoSQL database, and KinomaJS based on Javascript.

Freeboard is used to monitor IoT projects.

IoT in Banking, Financial, and Service Sector

With interconnected customer devices and operational systems, banks can oversee and analyze their customer’s financial transactions in real-time and act accordingly. In the case of sky-rocketing customer transactions, servers may come crashing down. Internally connected systems of IoT, from customer mobile devices to storage devices, prevents potential server issues and makes operations in the financial sector easier.

Customer insurance policies should monitor customer data, such as past and present health records. In the health sector, IoT can create a seamless brain-to-computer interface for paralyzed patients.

Components of financial services where we can deploy IoT include digitalizing work sites, transport systems, regulatory systems, foreign exchange, treasury bills, trading system, stocks, insurance policies, logistics, inventory control, and customer support.

Emerging trends in IoT in the financial services sector will play a key role in this digital landscape.