THE INTERNET OF THINGS: A SURVEY

Author(s):  
Luigi Atzori ◽  
Antonio Lera ◽  
Giacomo Morabito

This paper addresses the Internet of Things. Main enabling factor of this promising paradigm is the integration of several technologies and communications solutions. Identification and tracking technologies, wired and wireless sensor and actuator networks, enhanced communication protocols (shared with the Next Generation Internet), and distributed intelligence for smart objects are just the most relevant. As one can easily imagine, any serious contribution to the advance of the Internet of Things must necessarily be the result of synergetic activities conducted in different fields of knowledge, such as telecommunications, informatics, electronics and social science. In such a complex scenario, this survey is directed to those who want to approach this complex discipline and contribute to its development. Different visions of this Internet of Things paradigm are reported and enabling technologies reviewed. What emerges is that still major issues shall be faced by the research community. The most relevant among them are addressed in details.

2020 ◽  
Author(s):  
Tanweer Alam ◽  
Baha Rababah ◽  
Rasit Eskicioglu

Increasing the implication of growing data generated by the Internet of Things (IoT) brings the focus toward extracting knowledge from sensors’ raw data. In the current cloud computing architecture, all the IoT raw data is transmitted to the cloud for processing, storage, and control things. Nevertheless, the scenario of sending all raw data to the cloud is inefficient as it wastes the bandwidth and increases the network load. This problem can be solved by Providing IoT Gateway at the edge layer with the required intelligence to gain the Knowledge from raw data to decide to actuate or offload complicated tasks to the cloud. This collaboration between cloud and edge called distributed intelligence. This work highlights the distributed intelligence concept in IoT. It presents a deep investigation of distributed intelligence between cloud and edge layers under IoT architecture, with an emphasis on its vision, applications, and research challenges. This work aims to bring the attention of IoT specialists to distributed intelligence and its role to deduce current IoT challenges such as availability, mobility, energy efficiency, security, scalability, interoperability, and reliability.


Author(s):  
Baha Rababah ◽  
Tanweer Alam ◽  
Rasit Eskicioglu

Increasing the implication of growing data generated by the Internet of Things (IoT) brings the focus toward extracting knowledge from sensors’ raw data. In the current cloud computing architecture, all the IoT raw data is transmitted to the cloud for processing, storage, and control things. Nevertheless, the scenario of sending all raw data to the cloud is inefficient as it wastes the bandwidth and increases the network load. This problem can be solved by Providing IoT Gateway at the edge layer with the required intelligence to gain the Knowledge from raw data to decide to actuate or offload complicated tasks to the cloud. This collaboration between cloud and edge called distributed intelligence. This work highlights the distributed intelligence concept in IoT. It presents a deep investigation of distributed intelligence between cloud and edge layers under IoT architecture, with an emphasis on its vision, applications, and research challenges. This work aims to bring the attention of IoT specialists to distributed intelligence and its role to deduce current IoT challenges such as availability, mobility, energy efficiency, security, scalability, interoperability, and reliability.


2020 ◽  
Author(s):  
Baha Rababah ◽  
Tanweer Alam ◽  
Rasit Eskicioglu

Increasing the implication of growing data generated by the Internet of Things (IoT) brings the focus toward extracting knowledge from sensors’ raw data. In the current cloud computing architecture, all the IoT raw data is transmitted to the cloud for processing, storage, and control things. Nevertheless, the scenario of sending all raw data to the cloud is inefficient as it wastes the bandwidth and increases the network load. This problem can be solved by Providing IoT Gateway at the edge layer with the required intelligence to gain the Knowledge from raw data to decide to actuate or offload complicated tasks to the cloud. This collaboration between cloud and edge called distributed intelligence. This work highlights the distributed intelligence concept in IoT. It presents a deep investigation of distributed intelligence between cloud and edge layers under IoT architecture, with an emphasis on its vision, applications, and research challenges. This work aims to bring the attention of IoT specialists to distributed intelligence and its role to deduce current IoT challenges such as availability, mobility, energy efficiency, security, scalability, interoperability, and reliability.


2020 ◽  
Author(s):  
Vinod Kumar Verma

BACKGROUND COVID- 19 pandemics has affected the life of every human being in this world dramatically. The daily routine of the human has been changed to an uncertain extent. Some of the people are affected by the COVID-19, and some of the people are in fear of this epidemic. This has completely changed the thorough process of the people, and now, they are looking for solutions of this pandemic at different levels of the human addressable areas. These areas include medicine, vaccination, precautions, psychology, technology-assisted solutions like information technology, etc. There is a need to think in the direction of technology compliant solutions in the era of COVID-19 pandemic. OBJECTIVE The objective of this paper is to discuss the existing views and focus on the recommendations for the enhancement in the current situation from COVID-19. METHODS Based on the literature, perceptions, challenges, and viewpoints, the following opinions are suggested to the research community for the prevention and elimination of global pandemic COVID-19. The research community irrespective of the discipline focus on the following: 1. The comprehensive thought process for the designing of the internet of things (IoT) based solutions for healthcare applications used in the prevention from COVID-19. 2. Strategies for restricting outbreak of COVID-19 with the emerging trends in Ehealthcare applications. Which should be the optimal strategy to deal with a global pandemic? 3. Explorations on the data analysis as derived from the advanced data mining and warehousing associated with IoT. Besides, cloud-based technologies can be incorporated for the global spread of healthcare-related information to serve the community of different countries in the world. 4. The most adaptable method and technology can be deployed for the development of innovative solutions for COVID-19 related people like smart, patient-centric healthcare information systems. 5. Implementation of smart solutions like wearable technology for mask and PPE along with their disposal can be considered to deal with a global epidemic like COVID-19. This will lead to the manufacturing and incorporation of wearable technologies in the healthcare sector by industries. 6. A Pervasive thought process can be standardized for dealing with global pandemic like COVID-19. In addition, research measures should be considered for the security and privacy challenges of IoT services carrying healthcare-related information. These areas and directions are diverse but, in parallel, the need for healthy bonding and correlation between the people like researchers and scientists irrespective of their discipline. The discipline may vary from medical, engineering, computing, finance, and management, etc. In addition, standard protocols and interoperability measures can be worked out for the exchange of information in the global pandemic situations. RESULTS Recommendations Discussed CONCLUSIONS In this paper, the opinions have been discussed in the multi-disciplinary areas of research like COVID-19 challenges, medicines and vaccines, precautionary measures, technology assistance, and the Internet of Things. These opinions and discussion serve as an integrated platform for researchers and scientists to think about future perspectives to deal with healthcare-related COVID-19 pandemic situation. This includes the original, significant, and visionary automation based ideas, innovations, scientific designs, and applications focusing on Inter-disciplinary technology compliant solutions like IoT, vaccinations, manufacturing, preventive measures, etc. for the improvement of efficiency and reliability of existing healthcare systems. For the future, there is dire need to strengthen the technology not only in the one area but also for the interdisciplinary areas to recover from the pandemic situation rapidly and serve the community.


Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2417
Author(s):  
Andrzej Michalski ◽  
Zbigniew Watral

This article presents the problems of powering wireless sensor networks operating in the structures of the Internet of Things (IoT). This issue was discussed on the example of a universal end node in IoT technology containing RFID (Radio Frequency Identification) tags. The basic methods of signal transmission in these types of networks are discussed and their impact on the basic requirements such as range, transmission speed, low energy consumption, and the maximum number of devices that can simultaneously operate in the network. The issue of low power consumption of devices used in IoT solutions is one of the main research objects. The analysis of possible communication protocols has shown that there is a possibility of effective optimization in this area. The wide range of power sources available on the market, used in nodes of wireless sensor networks, was compared. The alternative possibilities of powering the network nodes from Energy Harvesting (EH) generators are presented.


2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Jun Huang ◽  
Liqian Xu ◽  
Cong-cong Xing ◽  
Qiang Duan

The design of wireless sensor networks (WSNs) in the Internet of Things (IoT) faces many new challenges that must be addressed through an optimization of multiple design objectives. Therefore, multiobjective optimization is an important research topic in this field. In this paper, we develop a new efficient multiobjective optimization algorithm based on the chaotic ant swarm (CAS). Unlike the ant colony optimization (ACO) algorithm, CAS takes advantage of both the chaotic behavior of a single ant and the self-organization behavior of the ant colony. We first describe the CAS and its nonlinear dynamic model and then extend it to a multiobjective optimizer. Specifically, we first adopt the concepts of “nondominated sorting” and “crowding distance” to allow the algorithm to obtain the true or near optimum. Next, we redefine the rule of “neighbor” selection for each individual (ant) to enable the algorithm to converge and to distribute the solutions evenly. Also, we collect the current best individuals within each generation and employ the “archive-based” approach to expedite the convergence of the algorithm. The numerical experiments show that the proposed algorithm outperforms two leading algorithms on most well-known test instances in terms of Generational Distance, Error Ratio, and Spacing.


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