Assignment First

  本篇论文代写价格-物联网系统讲了本研究旨在了解和完成芬兰合作项目的工业大数据应用物联网系统。大约有20家不同的公司参与了这个项目,他们的目标是创建一个未来的物联网网络。这项工作只考虑完成这个未来物联网系统的一个子系统。所考虑的子系统是基于RFID的远程识别与跟踪系统。本篇论文代写价格文章由加拿大第一论文 Assignment First辅导网整理,供大家参考阅读。

  Basen is the third main company here at Finland that works on these analytics solutions. Basen is an international company and transforms products to intelligent services. They work across different industries and hence provide a versatile set of products. Additionally, they have been in the industry for so long, that they would be able to bring expertise from many different industries into the logistics. In both the Finnish market and in the case of the Industrial market it is seen that Basen is fast becoming one of the primary platforms with respect to IoT technologies. They are also pioneers in the workings on Spime. While most Spime technologies are currently theoretical, when existing IoT and Big Data technologies combine then it presents much more solutions. An evolving algorithmic system is created here. Basen works on converting normal physical products into intelligent services. Now this company once again brings in as its strength, the experience it has gained over years being in the Software as service (SaaS) technology use and also in the case of developing Platform as a Service (PaaS) provider style of technologies in addition Basen increases the scalability of its working by offering services across different industries just as in the case of Conexbird. It offers a combination of architectures such as that of ICT, IoT and M2M combined.

  Given this background context in general, the current research aims at understanding and completing the IoT system for Big Data use in industrial working for a collaborative Finnish project. Around 20 different companies are involved in the project and they aim to create a futuristic IoT network. This work considers only the completion of a subsystem of this futuristic IoT system. The subsystem considered was that of long range identification and tracking system with the RFID. This research suggests that the use of the uhf tag will be of better benefit as it has the longest range as a passive transponder. Now this form of a tracking is beneficial for the company, as it ensures that the driver need not leave the cabin of the forklift (Chow, 2006). Now, this form of an operation is not exactly new, even in the context of the merging of IoT and Big data systems. For instance, in the context of internal maritime systems,it is noticed that they often make use of Long range identification and tracking LRIT systems. The LRIT is useful for collecting data from on the vessels such as their position information. The information received was big data as it was information received from many ships, over many hundreds of voyages. In the case of the maritime implemented LRIT, the National data centre will maintain all the data. Membership states that ships are 300 gross tons and travel within 1000 nautical miles or more of the US coast. In this context, the existing classified and unclassified systems do help in and integrated tracking watch. However, LRIT and components are useful in the context of improving the overall Maritime Domain Awareness. The long range tracking system led to an enhanced awareness. The LRIT complements are the existing components by bringing to Maritime tracking a satellite based real time tracking and reporting mechanism. Real time reporting introduces the need to handle the enormous amount of data that also come in at the same time (Hont, 2004).