China
Africa
Explore chapters and articles related to this topic
Artificial Intelligence in Healthcare
Published in Puneet Kumar, Vinod Kumar Jain, Dharminder Kumar, Artificial Intelligence and Global Society, 2021
Ajay Kumar Yadav, Rajesh Mamilla
The machine learning algorithm uses a lot of data to train machines to think. These are comprised of several types of data and come from various sources (human-generated data and from IOT devices). Business analytics and ML algorithm are used in the background of data processing to find hidden patterns from data that will add value to organizations. AI can be used to identify medical fraud (whether the patient is really sick or not). Since we get the data from several IOT sources and customer habits, prediction of sickness can be estimated by AI tools. 5G technology would transfer data 100 times faster compared to current cellular network speed. The rapid data transmission from client to server would help AI to process the task quicker. 5G would help take more real-time decisions as the algorithm can be optimized with more real-time data to give instantaneous suggestions to the user. With an increase in the number of sensors that collects data from human, the business healthcare sector can segregate people by health risk and formulate common policy.
Propagation over Earth
Published in Fei Hu, Magnetic Communications, 2018
Mohammad N. Abdallah, Tapan K. Sarkar, Salazar-Palma Magdalena
Now we can discuss how we can benefit from the previous analysis to study propagation over Earth in practical scenarios like the cellular network case. Cellular networks are based on dividing a given area into smaller cells, and each one of these cells is fed by a specific base station. This aims to serve a large number of subscribers with a small number of available channels. It turns out that the propagation path loss exponent is the essential factor in planning how to divide a given area into cells. The path loss exponent will give the designer an idea how the signal strength will change while moving away from the base station; so it is important to know whether the base station can radiate sufficient power to reach the desired subscribers of that area. At the same time, there will be neighboring base stations that use the same frequency channels to support their subscribers. Thus, the interference level must be kept under some threshold level to guarantee high Quality of Service (QoS) in the cell of interest. The drive test data in cellular networks is crucial for providing information about the real performance of any network, as they illustrate how the signal strength varies while moving away from the base station. The philosophy of channel modeling describes methodologies to predict the performance of a base station antenna inside a given cell. Despite large efforts being made in the field of channel modeling, drive tests data remain irreplaceable, as this checks the accuracy of the model to predict the propagation path loss inside a cell.
The Beginning
Published in Saad Z. Asif, 5G Mobile Communications Concepts and Technologies, 2018
A cellular network or mobile network is a wireless network spread over the land through a web of cell sites. Each of these sites or cell towers is comprised of a transceiver (transmitter/receiver) for communications with mobile devices. From a technological perspective, mobile devices† rely on die hard cellular towers for communications and these cell sites or cell towers are designed to keep a hexagonal shape in mind. The use of hexagonal cells was invented by Bell Laboratories in the 1970s [2]. This shape was selected over other geometrical shapes since by using it the cells can be laid next to each other with no overlap, thus providing coverage theoretically to the entire service area without any gaps [3]. The hexagon design has been at least so far remained as necessary for mobile communications as cement for the construction of buildings or coal tar for carpeting the roads.
Smart logistics based on the internet of things technology: an overview
Published in International Journal of Logistics Research and Applications, 2021
Yangke Ding, Mingzhou Jin, Sen Li, Dingzhong Feng
IoT technology has been developing in performance and function. Many anti-collision algorithms for RFID tags have been constructed to avoid tag collisions (Chen 2015; Su et al. 2018; Chen and Zhao 2019), and several novel protocols have been proposed to identify the missing tags (Chen, Xue, and Wang 2017; Shahzad and Liu 2016). The sensor’s battery life can be extended by optimising communication protocols and by in-network preprocessing of the sensor data (Jedermann, Pötsch, and Lloyd 2014). In addition to the improvement of IoT, its supporting technologies are making great progress. Internet Protocol version 6 (IPv6) uses 128-bit (16-byte) addresses whose space supports approximately 340 undecillion addresses (Wollschlaeger, Sauter, and Jasperneite 2017). These almost inexhaustible addresses provide tremendous support for the addressing of any number of objects needed in IoT. The coming fifth-generation of cellular networks (5G) brings greater speed (to move more data), lower latency (to be more responsive), and lower energy and cost (to be economical) than ever before (Andrews et al. 2014). 5G architecture is expected to accommodate a wide range of use cases in IoT with higher requirements for latency, resilience, coverage, and bandwidth. However, there is no end to the development of technology and the actual demand. It is a research need to further solve the above tough issues of IoT in Section 4.
Digital technology enablers and their implications for supply chain management
Published in Supply Chain Forum: An International Journal, 2020
As technology changes the world around us, society will come to rely more and more on high-speed, low latency, secure connectivity that is ubiquitous and reliable. The latency and speed limitations of current technologies (4 G and wired networks) are the predominant reasons hindering the ability of enterprises to move towards a decentralised workforce. Fifth-generation cellular networks (5 G) will deliver mobile data services that will always be available to customers where and when they need them. Commercial 5 G networks will be widely deployed by 2020; that will herald in an era when the vision of ubiquitous Internet access is close to reality. Technologies like hyper-fast 3D printer, an AI-powered 5 G security camera to replace front desk staff, and AI-powered conference room will enable ultra-smart workplaces. The increased speed of 5 G combined with its lower power consumption and ability to move large amounts of data with minimal delay is fulling many technologies and makes them real.
Latency and Energy Efficient Bio-Inspired Conic Optimized and Distributed Q Learning for D2D Communication in 5G
Published in IETE Journal of Research, 2023
Sridhar Varadala, S. Emalda Roslin
The fifth-generation (5G) cellular networks has been developed to fulfill the need of the future generation by appreciably managing data traffic, which is produced because of the escalating number of mobile devices and their bandwidth intensive real time applications. The nature of the 5G networks system comprises excessive volume, tremendously low latency, and immense data rate for maintaining several media intensive real time operations along with demanding Quality of Service (QoS) specifications.