Towards the Digital Twin (DT) of narrow-band Internet of Things (NBIoT) wireless communication in industrial indoor environment

A study of the behavior of NB-IoT wireless communication in an industrial indoor environment was conducted in this paper. With Wireless Insite software, a scenario in the industrial sector was simulated and modeled. Our research examined how this scenario or environment affected the communication parameters of NB-IoT’s physical layer. In this context, throughput levels among terminals as well as between terminals and transceiver towers, the power received at signal destination points, signal-to-noise ratios (SNRs) in the environment, and distances between terminals and transceivers are considered. These simulated results are also compared with the calculated or theoretical values of these parameters. The results show the effect of the industrial setting on wireless communication. The differences between the theoretical and simulated values are also established

A digital twin (DT) approach to narrow-band Internet of things (NB-IoT) wireless communication optimization in an industrial scenario

The pervasive realization of virtual replication of physical entities termed Digital Twin (DT) has been utilized in this paper to optimize the wireless communication of the Narrowband Internet of Things (NB-IoT) in an industrial scenario. This optimization is exclusively achieved through DT approach. NB-IoT is a Low-Powered Wide Area Network (LPWAN) standardized by 3GPP and leverages Long Term Evolution (LTE) technology. The Amplify-and-Forward (AF) optimization technique is used to improve the performance of some notably poor-performing terminals in the scenario. Bit-Error-Rate (BER) tests show the terminals’ overall performance before and after optimization. An improvement of 17% is achieved in BER. The signal quality of the channels is analyzed as well as the Cumulative Distribution Function (CDF) is used to showcase the effective throughput performance of the NB-IoT terminals

Suitability of NB-IoT for indoor industrial environment: a survey and insights

The Internet of Things (IoT) and its applications in industrial settings are set to bring in the fourth industrial revolution. The industrial environment consisting of high profile manufacturing plants and a variety of equipment is inherently characterized by high reflectiveness, causing significant multi-path components that affect the propagation of wireless communications—a challenge among others that needs to be resolved. This paper provides a detailed insight into Narrow-Band IoT (NB-IoT), Industrial IoT (IIoT), and Wireless Sensor Networks (WSN) within the context of indoor industrial environments. It presents the applications of NB-IoT for industrial settings, such as the challenges associated with these applications. Furthermore, future research directions were put forth in the areas of NB-IoT network management using self-organizing network (SON) technology, edge computing for scalability enhancement, security in NB-IoT generated data, and proposing a suitable propagation model for reliable wireless communications

Participatory Research for Low-resourced Machine Translation:A Case Study in African Languages

Research in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved. "Low-resourced"-ness is a complex problem going beyond data availability and reflects systemic problems in society. In this paper, we focus on the task of Machine Translation (MT), that plays a crucial role for information accessibility and communication worldwide. Despite immense improvements in MT over the past decade, MT is centered around a few high-resourced languages. As MT researchers cannot solve the problem of low-resourcedness alone, we propose participatory research as a means to involve all necessary agents required in the MT development process. We demonstrate the feasibility and scalability of participatory research with a case study on MT for African languages. Its implementation leads to a collection of novel translation datasets, MT benchmarks for over 30 languages, with human evaluations for a third of them, and enables participants without formal training to make a unique scientific contribution. Benchmarks, models, data, code, and evaluation results are released under https://github.com/masakhane-io/masakhane-mt

An Assessment of household water accessibility in the Southern part of Niger State, Nigeria

No Abstract

NB-IoT Performance Analysis and Evaluation in Indoor Industrial Environment

No abstract available

Leveraging on the genomics and immunopathology of SARS-CoV-2 for vaccines development: prospects and challenges

The incidence and case-fatality rates (CFRs) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, the etiological agent for Coronavirus Disease 2019 (COVID-19), have been rising unabated. Even though the entire world has been implementing infection prevention and control measures, the pandemic continues to spread. It has been widely accepted that preventive vaccination strategies are the public health measures for countering this pandemic. This study critically reviews the latest scientific advancement in genomics, replication pattern, pathogenesis, and immunopathology of SARS-CoV-2 infection and how these concepts could be used in the development of vaccines. We also offer a detailed discussion on the anticipated potency, efficacy, safety, and pharmaco-economic issues that are and will be associated with candidate COVID-19 vaccines