The Internet of Things is a paradigm where everyday objects can be equipped with identifying, sensing, networking and processing capabilities that will allow them to communicate with one another and with other devices and services over the Internet to accomplish some objective. Ultimately, IoT devices will be ubiquitous, context-aware and will enable ambient intelligence. This article reports on the current state of research on the Internet of Things by examining the literature, identifying current trends, describing challenges that threaten IoT diffusion, presenting open research questions and future directions and compiling a comprehensive reference list to assist researchers.

The Internet of Things--A survey of topics and trends

This article is focused on the importance and influence of Industry 4.0 and consequently the Internet-connected technologies for the creation of value added for organizations and society. The contribution of the article is mainly conceptual. With the development of the Internet, the Internet of things that is central to the new industrial revolution has led to “Industry 4.0.” The aim of this article is to synthesize the known theory and practices of Industry 4.0, and to investigate the changes that will result from Industry 4.0 and with the development of the Internet of things.

https://journals.sagepub.com/doi/pdf/10.1177/2158244016653987

A Complex View of Industry 4.0

This paper surveys the state of the art on the use and research of cloud computing in education following a systematic methodology. After a comprehensive search of the scientific literature, 112 works were selected for the review. The survey identifies and analyzes the advantages and risks that the use of cloud computing may have for the main stakeholders in education, which can be useful to identify the scenarios in which the use of cloud computing in an educational context may have significant advantages. Furthermore, the survey categorizes and discusses the main technical and domain-specific research challenges, thus facilitating researchers the task of finding relevant issues, in which they can focus their efforts. We review 112 scientific works on cloud computing in education up to 2012.The survey takes into account the main educational stakeholders.Advantages and risks of cloud in education are categorized and exemplified.We identify and discuss promising technical and domain-specific research issues.

Cloud computing and education

Utilizing online learning resources (OLR) from multi channels in learning activities promise extended benefits from traditional based learning-centred to a collaborative based learning-centred that emphasises pervasive learning anywhere and anytime. While compiling big data, cloud computing, and semantic web into OLR offer a broader spectrum of pervasive knowledge acquisition to enrich users' experience in learning. In conventional learning practices, a student is perceived as a recipient of information and knowledge. However, nowadays students are empowered to involve in learning processes that play an active role in creating, extracting, and improving OLR collaborative learning platform and knowledge sharing as well as distributing. Researchers have employed contents analysis for reviewing literatures in peer-reviewed journals and interviews with the teachers who utilize OLR. In fact, researchers propose pervasive knowledge can address the need of integrating technologies like cloud computing, big data, Web 2.0, and Semantic Web. Pervasive knowledge redefines value added, variety, volume, and velocity of OLR, which is flexible in terms of resources adoption, knowledge acquisition, and technological implementation.

Developing online learning resources: Big data, social networks, and cloud computing to support pervasive knowledge

The proposed model manages travels and cargos, without user interaction.We developed a hardware that obtains context information using RFID technology.The model uses context information and geofencing algorithms to perform decisions.The model sends notifications, speeding decision-making up, and reducing costs. The cargo transport represents the largest share of logistics costs in most companies. Consequently, companies are investing in tracking and tracing systems aiming to improve services, reduce costs and ensure the safety in cargo transportation. To play a part in this area, we propose in this article SafeTrack, a model for logistics management based on geofencing algorithms and radio-frequency technology. In this approach, the focus is on dealing with delivery management. The main scientific contribution of SafeTrack is automatic delivery management. Besides dealing with deliveries without user interaction, we provide a mechanism to detect inconsistencies at real-time. Furthermore, the model monitors detours in planned routes and deals with alarms notifications using mobile devices. To provide that features, we employed Geofence concept with two solutions that enable to detect, in real-time, the occurrence of detours in planned routes. We also created a component, named SafeDuino, to control loads delivery and pickups. The decision on the occurrence of inconsistencies during the logistics flow is performed through the fusion of context information, obtained from SafeDuino and a mobile device, using radio-frequency technology. We built a complete and functional prototype, which was evaluated in a controlled environment, testing several conditions. The test scenario was executed twenty times, showing that the proposed model is capable to identify all inconsistencies along the travels. We concluded that SafeTrack improves logistics operation, optimizing decision-making, avoiding losses during the logistics flow, and also allowing companies to remain competitive in the market.

An intelligent model for logistics management based on geofencing algorithms and RFID technology

At present, most of conventional education forms are becoming not being suitable for requirements of social progress and educational development and not being able to catch up with the changes of learning demand in time, thus computer networks have brought opportunities for it. However, in traditional web-based e-learning mode, system construction and maintenance are located in interior of educational institutions or enterprises, which results in a lot of problems existed, such as a lot of investment needed, but without capital gains to return, without development potential and staying power. Cloud computing that introduces efficient scale mechanism can let construction of e-learning system be entrusted to suppliers and provide a new mode for e-learning. In this paper, we introduced cloud computing to e-learning, built an e-learning cloud, and made an active research and exploration for it from the following aspects: its work mode, architecture, construction method, external interface with the business model, challenges and solutions etc. Our results suggest that the introduction of cloud computing into e-learning is feasible and it can greatly improve the efficiency of investment and the power of management, which can make e-learning system development into a virtuous circle and achieve a win-win situation for suppliers and customers.

Cloud Computing: A New Business Paradigm for E-learning

In this paper, a modern logistics monitoring platform based on the Internet of Things was studied and its system architecture and functions were particularly designed. The platform was designed based on the following technologies. In aspect of goods identification, a global unified electronic product code EPC was adopted and each goods was given a unique code that was according with international standards. Reading and writing EPC data was by taking use of RFID technology, which read data from electronic tags via a wireless non-contact method. In aspect of goods code management, new concepts of dynamic EPC and static EPC were proposed for goods in transport and movement. Through introduction of dynamic EPC and static EPC, data flow significantly was reduced, the management process was simplified and management efficiency was improved. In aspect of network transmission, both wired network and wireless network were taken for transmission task. Wired networks were available based on Internet and LAN. For mobile sites, wireless network GRPS was used for communication. In aspect of positioning goods, global positioning system GPS was used for location and tracking of goods. In aspect of platform function design, the system’s function requirements were analyzed and designed, and a series of its functions were proposed, such as real-time data acquisition, automatic alarm, remote control, data control and processing, historical information record and product quality safety tracing, market analysis and intelligent projections etc.. Modern logistics monitoring platform based on the Internet of Things, because of its advanced technologies, excellent performances and integrated functions, would play an important role in the development of modern logistics.

Modern Logistics Monitoring Platform Based on the Internet of Things

In this paper, on the basis of full investigation and a lot of comparison with expert systems at home and abroad, introducing Web technology, WebGIS and BP neural network technology into expert system and taking full use of their respective advantages, we have designed and developed a remote diagnosis and control expert system for citrus agricultural diseases and insect pests based on WebGIS and BP neural network. We put emphases on the design of forward inference engine based on neural network and reverse inference engine based on rule system. In the whole expert system, neural network serves as a forward inference engine for the expert system. It accepts standardized raw data input of the diseases and insect pests and gives the diagnosis conclusion after reasoning process. Reverse reasoning is made by rule system, which is going to verify the diagnosis conclusions provided by neural network. In this way, the reasoning speed of entire system and correct diagnosis rate are greatly increased. At the same time, the rule system provides control methods for diseases and insect pests according to the diagnosis conclusions and also provides its geographical distribution information based on GIS. The experimental results show that the expert system has an accurate and reliable performance, so it has a good promotion prospects for applications.

Remote Diagnosis and Control Expert System for Citrus Agricultural Diseases and Insect Pests Based on BP Neural Network and WebGIS

General sharing of information resources on the Internet has already be achieved through Internet technology. But the goal of grid is trying to achieve a comprehensive connectivity and sharing for all resources on the Internet, providing high-performance computing services for users. In this paper, grid resource scheduling was studied and according to the current research about it some innovation and improvement for it were made from the following aspects.

Multi-polar Autonomous System Grid Resource Scheduling Model and Algorithm Based on Multi-agent and GA

According to the characteristics of production and processing of sea food shrimp,an intelligent general predictive platform for sea food microorganism growth was designed and developed,which could provide an analysis method for sea food safety production and pro-cessing.

Wang Zhengxia

Papers

Cloud Computing: A New Business Paradigm for E-learning

Modern Logistics Monitoring Platform Based on the Internet of Things

Remote Diagnosis and Control Expert System for Citrus Agricultural Diseases and Insect Pests Based on BP Neural Network and WebGIS

Multi-polar Autonomous System Grid Resource Scheduling Model and Algorithm Based on Multi-agent and GA

Intelligent General Predictive Platform for Sea Food Microorganism Growth