This trend is called “the device mesh.” With this, there will be a move away from the traditional machines and devices like desktop and mobiles to include the wide “range of endpoints” that would be used by the humans for interaction. There will be an expansion of connection models, and greater interaction among the devices. There will be a massive development in the augmented reality and the wearables.
All the digital interactions can get “synchronized into a continuous and ambient digital experience that preserves our experience across traditional boundaries of devices, time and space.” The organizations would then have to consider the behavior journeys of their customers to shift their focus from the designs from the discrete apps to the full range of services and products that are associated with the user experience.
The advancement of 3D printing will continue with different types of materials such as carbon fiber, conductive ink, glass, pharmaceuticals, electronics, biological materials etc. Its practical application would expand to include medical, military, energy, automotive and aerospace fields respectively.
Everything that surrounds us and the digital mesh is not only producing, but communicating and using the virtual information which is not measurable. The organizations have to learn certain important things – what type of information will provide strategic value, how data can be accessed from various sources etc.
Only advanced level of machine learning can make the smart machines work with more intelligence when the latter will be learning as well as understanding the concepts of the environment. This field is developing fast and it is up to the organizations how they would apply the technologies to earn higher profits.
The advanced level of machine learning also enables the smart machines with several types of implementations such as autonomous vehicles, robots, smart advisors and virtual personal assistants (VPAs). These act, either autonomously or semi-autonomously making the autonomous agent as the main user interface. Thus, the user will now speak to any app rather than interact with the buttons and menus of a smartphone.
There has been a significant increase in the potential threats that an organization can encounter. The main reasons for this include emerging business of hackers and complex algorithmic economy and digital business. IT companies should concentrate on identifying and countering the threats along with the traditional measures like blocking to avoid attacks.
The smart machines and the digital mesh need intense demands in computing architecture to suit the requirements of the organizations. They can get this from the neuromorphic architectures that are ultra-efficient. The systems that are built on GPUs (graphics processing units) and FPGAs (field-programmable gate-arrays) will start functioning like our brains; this is mainly to undertake deep learning and pattern matching algorithms that are used by the smartphones.
The apps and the services can deliver to the dynamic and flexible environment of the digital mesh because of the service architecture and mesh app. This architecture will develop further to serve the evolving requirements of the users.
IoT platforms are a suite of components that enable: Deployment of applications that monitor, manage, and control connected devices. Remote data collection from connected devices. Independent and secure connectivity between devices. They will collect all the data from the endpoints from a technological and an architectural standpoint to realize the IoT.