دانلود رایگان مقاله انگلیسی اینترنت اشیا و کلان داده ها - قطع زنجیره ی ارزش و رشد اکوسیستم ها - الزویر 2016

Abstract:

IoT connects devices, humans, places, and even abstract items like events. Driven by smart sensors, powerful embedded microelectronics, high-speed connectivity and the standards of the internet, IoT is on the brink of disrupting today’s value chains. Big Data, characterized by high volume, high velocity and a high variety of formats, is a result of and also a driving force for IoT. The datafication of business presents completely new opportunities and risks. To hedge the technical risks posed by the interaction between “everything”, IoT requires comprehensive modelling tools. Furthermore, new IT platforms and architectures are necessary to process and store the unprecedented flow of structured and unstructured, repetitive and non-repetitive data in real-time. In the end, only powerful analytics tools are able to extract “sense” from the exponentially growing amount of data and, as a consequence, data science becomes a strategic asset.

11. CONCLUSIONS

Sensor technology – from simple proximity measuring to complex bio-sensing– is developing fast. Numerous connectivity standards are available. In this document the focus is on the need for software standardization and the contribution of software platforms to handle the unprecedented complexity of applications. Data, created by sensors, must be enriched by meta-data to provide meaning. Programming languages, data encoding formats and protocols need to be regarded with respect to their relevance for IoT. Identity management for devices, users, application and services has to be addressed. To verify data and metadata, their provenance and the location of the sensors are relevant. The modelling of these tightly interconnected items leads to further questions.

IoT is on a fast accelerating path with evolving standards, technologies and platforms. As of Jan 2016, with over 275 vendors and products in the data platform and analytics landscape (451 Research 2016) it is no surprise that IoT and Big Data suffers from a lack of interoperability with data silos, high costs and limited market potential.