Peer-reviewed journal on social and business aspects of informatics that covers the theory and application of enterprise information systems, as well as interactions between ICT and people.

Currently, the Internet of Things (IoT) is the most contentious research subject. However, IoT still suffers from many security problems, and the security concerns are overgrowing with substantial IoT deployment. IoT will remain in danger unless understanding and addressing the security challenges. For this reason, this paper implements a full view of the IoT architecture and describes the characteristics and functionality of each layer. For a deeper understanding of IoT security challenges, we focus on identifying security requirements, and vulnerabilities in each IoT layer. Also, we discuss and classified the different security attacks in IoT.

Purpose: This research paper aims at proposing a framework based on semantic integration in Big Data for saving energy in smart cities. The presented approach highlights the potential opportunities offered by Big Data and ontologies to reduce energy consumption in smart cities.Design/methodology/approach: This study provides an overview of semantics in Big Data and reviews various works that investigate energy saving in smart homes and cities. To reach this end, we propose an efficient architecture based on the cooperation between ontology, Big Data, and Multi-Agent Systems. Furthermore, the proposed approach shows the strength of these technologies to reduce energy consumption in smart cities.Findings: Through this research, we seek to clarify and explain both the role of Multi-Agent System and ontology paradigms to improve systems interoperability. Indeed, it is useful to develop the proposed architecture based on Big Data. This study highlights the opportunities offered when they are combined together to provide a reliable system for saving energy in smart cities.Practical implications: The significant advancement of contemporary applications (smart cities, social networks, health care, IoT, etc.) requires a vast emergence of Big Data and semantics technologies in these fields. The obtained results provide an improved vision of energy-saving and environmental protection while keeping the inhabitants’ comfort.Originality/value: This work is an efficient contribution that provides more comprehensive solutions to ontology integration in the Big Data environment. We have used all available data to reduce energy consumption, promote the change of inhabitant’s behavior, offer the required comfort, and implement an effective long-term energy policy in a smart and sustainable environment.

Artificial Intelligence is revolutionizing the world. In the last decades, it is applied in almost all fields especially in medical prediction. Researchers in artificial intelligence have exploited predictive approaches in the medical sector for its vital importance in the process of decision making. Medical prediction aims to estimate the probability of developing a disease, to predict survivability and the spread of a disease in an area. Prediction is at the core of modern evidence-based medicine, and healthcare is one of the largest and most rapidly growing segments of AI. Application of technologies such as genomics, biotechnology, wearable sensors, and AI allows to: In this research, an overview of applied methods on the management of diseases is presented. The most used methods are Artificial Intelligence methods such as machine learning and deep learning techniques which have improved diagnosis and prognosis efficiency.

Mobile learning is considered a new phase of e-learning which gives the opportunity to learn more effectively and efficiently. In addition, the use of mobile devices for leaning is more sophisticated and more useful. The m-learning has become available anywhere and anytime for all students and professors. Moreover, the features of these mobile devices include ease of use in every place and time, very reasonable cost for students, and the ability to communicate through the internet or mobile networks, encouraging the development of many kinds of methods and systems. Now, a huge number of applications, in several domains, are oriented to this kind of mobile device. Researchers have been exploiting this technology to enhance the knowledge of learner (especially foreign languages learning). In this paper, the author proposed an educational system that provides the opportunity for students to learn English language outside the classroom and encourages them to get actively involved in their own learning processes.

In this paper, we propose a novel, secure, and intelligent IoT approach based on agent, we have implemented in the health care domain, where we developed an intelligent patient monitoring system for monitoring the patients heart rate automatically. Our system is more intelligent that can anticipate the critical condition before it even happens, send a message to the patient family, doctors, nurses, as well as hospital in-charge personal, and launch an alarm to be assisted by the nearest people in place. Also, our architecture ensures the authentication, authorization, and data sensing confidentiality. Hospitals and medical clinics can utilize our system to monitor their outpatients who are in danger of unpredictable health conditions. The approach presented in the paper can also be applied to other IoT domains.