ps代写：大数据
大数据具有量、速度、多样性的特点，与物联网相结合既带来了独特的机遇，也带来了挑战。物联网技术将利用这三个主要特征的结合。速度、体积和变化以不同的方式受到影响。因此，本研究对工业系统中使用的物联网大数据系统进行了表征和分析(Raza, 1999)。该研究特别借鉴了在实验室环境下使用RFID进行叉车操作的个人工作经验。这是一个与萨沃尼亚应用科学大学和Sigma oy合作进行的项目，萨沃尼亚oy的应用是在Sigma oy。上下文中的场景是使用RFID阅读器和超高频标签作为物联网系统的一部分，这对公司的叉车操作非常有用。除了添加物联网功能外，这里还添加了身份验证和授权等其他元素。
ps代写：大数据
工业需求的不同形式意味着物联网应用程序在如何满足这些需求方面有很多定制。就工业而言，可以将智能城市、电网或组织运输组合在一起。这里涉及到从实时监控到分析的各种相互关联的东西。在实时监控中，不同的设备做什么，他们的工作条件，他们的问题，他们的负载，他们的配置，等等被理解(Hont, 2004)。组织将能够进行所谓的预测性维护，即在开始之前修复问题。在配置、与人的交互、能源效率和最适合不同用途的东西方面，可以进行更好的优化。分析是用来找出物联网下一个版本设计的当前缺陷。现在，随着物联网应用在许多国家得到更广泛的应用，这项工作的重点一直放在芬兰的一家公司上，因此物联网项目、改进环境和更多的东西都是从芬兰的目标本身考虑的。
ps代写：大数据
Big data is characterized by volume, velocity and variety which when combined with the Internet of Things IoT presents unique opportunities as well as challenges. IoT technologies will make use of the combinations of the three main characteristics. Velocity, volume and variety are impacted on in different ways. IoT Big data systems such as the ones made use of in Industrial system hence are characterized and analysed in this study (Raza, 1999). The study in particular draws from personal work experience on a project using RFID for forklift operations that was conducted within laboratory settings. This was a co-working project carried out with the Savonia University of Applied Science and Sigma oy, where the application context was for Savonia Oy. The scenario in context is that of making use of RFID readers along with the UHF tag as part of an IoT system that would be useful for forklift operations at the company. Along with the IoT added functionality, additional elements such as that of authentication and authorization are also added here.
ps代写：大数据
The different forms of Industrial requirements mean that there is much customization in how IoT applications are characterized as such to meet those requirements. In the case of industries, a smart city, grid or organizational transport might be put together. There are interconnected different things involved here from that of real time monitoring to analytics. In real time monitoring, what different devices do, their operating conditions, their issues, their load, their configuration, etc. are understood (Hont, 2004). The organization would be able to do what is called predictive maintenance where they can fix issues before they start. Better optimization is possible in terms of configuration, interaction with humans, energy efficiency and most suitable things for different uses. Analytics is made use of to find out the current shortcomings for the design of the next versions of IoT things. Now with IoT application finding a broader range of use in many countries, the focus of this work has been on a company in Finland and hence the IoT projects, the improvements context and more are considered from the country of Finland objective as such.
