Best Practices

Author(s):  
Anchitaalagammai J. V. ◽  
Kavitha S. ◽  
Murali S. ◽  
Padmadevi S. ◽  
Shanthalakshmi Revathy J.

The internet of things (IoT) is rapidly changing our society to a world where every “thing” is connected to the internet, making computing pervasive like never before. It is increasingly becoming a ubiquitous computing service, requiring huge volumes of data storage and processing. Unfortunately, due to the lack of resource constraints, it tends to adopt a cloud-based architecture to store the voluminous data generated from IoT application. From a security perspective, the technological revolution introduced by IoT and cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. This chapter focus on security considerations for IoT from the perspectives of cloud tenants, end-users, and cloud providers in the context of wide-scale IoT proliferation, working across the range of IoT technologies. Also, this chapter includes how the organization can store the IoT data on the cloud securely by applying different Access control policies and the cryptography techniques.

Author(s):  
Reema Abdulraziq ◽  
Muneer Bani Yassein ◽  
Shadi Aljawarneh

Big data refers to the huge amount of data that is being used in commercial, industrial and economic environments. There are three types of big data; structured, unstructured and semi-structured data. When it comes to discussions on big data, three major aspects that can be considered as its main dimensions are the volume, velocity, and variety of the data. This data is collected, analysed and checked for use by the end users. Cloud computing and the Internet of Things (IoT) are used to enable this huge amount of collected data to be stored and connected to the Internet. The time and the cost are reduced by means of these technologies, and in addition, they are able to accommodate this large amount of data regardless of its size. This chapter focuses on how big data, with the emergence of cloud computing and the Internet of Things (IOT), can be used via several applications and technologies.


Author(s):  
Marwa Mahfodh Abdulqadir ◽  
Azar Abid Salih ◽  
Omar M. Ahmed ◽  
Dathar Abas Hasan ◽  
Lailan M. Haji ◽  
...  

The rapid advancement in the Internet of things applications generates a considerable amount of data and requires additional computing power. These are serious challenges that directly impact the performance, latency, and network breakdown of cloud computing. Fog Computing can be depended on as an excellent solution to overcome some related problems in cloud computing. Fog computing supports cloud computing to become nearer to the Internet of Things. The fog's main task is to access the data generated by the IoT devices near the edge. The data storage and data processing are performed locally at the fog nodes instead of achieving that at cloud servers. Fog computing presents high-quality services and fast response time. Therefore, Fog computing can be the best solution for the Internet of things to present a practical and secure service for various clients. Fog computing enables sufficient management for the services and resources by keeping the devices closer to the network edge. In this paper, we review various computing paradigms, features of fog computing, an in-depth reference architecture of fog with its various levels, a detailed analysis of fog with different applications, various fog system algorithms, and also systematically examines the challenges in Fog Computing which act as a middle layer between IoT sensors or devices and data centers of the cloud.


2018 ◽  
Vol 6 (3) ◽  
pp. 359-363
Author(s):  
A. Saxena ◽  
◽  
S. Sharma ◽  
S. Dangi ◽  
A. Sharma ◽  
...  

Author(s):  
Kai Zhang

With the development of emerging technology innovations such as the internet of things, classroom management has also shown an informatization trend. Among them, smart classrooms are an important part of the current university information environment construction. The purpose of this article is to build a smart classroom into an intelligent teaching environment with many functions such as intelligent perception and identification, real-time monitoring based on the internet of things technology and cloud computing technology. A questionnaire survey was conducted among freshman students in some majors, and interviews were conducted with the instructors. It was found that 92.19% of the students were satisfied with the classroom learning in the smart classroom environment, and most teachers thought that the teaching effect had been improved. Experiments have proven that the operation of smart classrooms based on the internet of things and cloud computing realizes the intelligence of teaching management services and improves the level of education informationization in schools.


Author(s):  
Leila Zemmouchi-Ghomari

Industry 4.0 is a technology-driven manufacturing process that heavily relies on technologies, such as the internet of things (IoT), cloud computing, web services, and big real-time data. Industry 4.0 has significant potential if the challenges currently being faced by introducing these technologies are effectively addressed. Some of these challenges consist of deficiencies in terms of interoperability and standardization. Semantic Web technologies can provide useful solutions for several problems in this new industrial era, such as systems integration and consistency checks of data processing and equipment assemblies and connections. This paper discusses what contribution the Semantic Web can make to Industry 4.0.


2021 ◽  
Vol 19 (3) ◽  
pp. 163
Author(s):  
Dušan Bogićević

Edge data processing represents the new evolution of the Internet and Cloud computing. Its application to the Internet of Things (IoT) is a step towards faster processing of information from sensors for better performance. In automated systems, we have a large number of sensors, whose information needs to be processed in the shortest possible time and acted upon. The paper describes the possibility of applying Artificial Intelligence on Edge devices using the example of finding a parking space for a vehicle, and directing it based on the segment the vehicle belongs to. Algorithm of Machine Learning is used for vehicle classification, which is based on vehicle dimensions.


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