The potential of indoor unmanned aerial vehicle (UAV) localization is paramount for diversified applications within large industrial sites, such as hangars, malls, warehouses, production lines, etc. In such real-time applications, autonomous UAV location is required constantly. This paper comprehensively reviews radio signal-based wireless technologies, machine learning (ML) algorithms and ranging techniques that are used for UAV indoor positioning systems. UAV indoor localization typically relies on vision-based techniques coupled with inertial sensing in indoor Global Positioning System (GPS)-denied situations, such as visual odometry or simultaneous localization and mapping employing 2D/3D cameras or laser rangefinders. This work critically reviews the research and systems related to mini-UAV localization in indoor environments. It also provides a guide and technical comparison perspective of different technologies, presenting their main advantages and disadvantages. Finally, it discusses various open issues and highlights future directions for UAV indoor localization.

Due to the vast rise of users, the variety of application requirements, and the enormous necessity for ubiquitous connectivity anytime and anywhere, integration of new technologies and ideas are required. Therefore, Device to Device (D2D) communication technology has been regarded as a critical concern for Beyond Fifth Generation (B5G) networks. In the D2D technology, devices in close proximity may connect without using a Base Station (BS). Consequently, improving the capacity and performance of traditional networks. The major objectives are to accomplish a high geared data rate, increase the network coverage with low latency, and improve Energy Efficiency (EE) and Spectrum Efficiency (SE). However, the coexistence of D2D technology in the traditional network can pose many issues and challenges, such as power control, interference, spectrum access, security, and mode selection. Consequently, a comprehensive survey that includes an investigation of the current issues in D2D technology is required. In this survey, we present a new categorization of the most important aspects of resource management in B5G D2D communication, such as power allocation, spectrum allocation, interference management, and mode selection. Furthermore, we discuss the limitations and open issues of the current techniques and propose a model approach and future directions for D2D communication in B5G wireless networks. Our survey aims to assist researchers in exploring and improving D2D communication within the framework of forthcoming wireless networks.

All businesses have many issues, especially small and medium enterprises trying to survive with traditional technology. Therefore, enterprises need to adopt business intelligence by using the management of information technology systems to overcome the issues. This study proposes a conceptual framework that identifies the potential factors that influence the adoption of business intelligence systems in the SME industry in Libya. Therefore, this study was established based on two main theories: the technology acceptance model (TAM) and the unified theory of adopting and using technology (UTAUT). In line with the previous studies that investigated this type of influence, this study recommended a conceptual framework containing several factors: change management, knowledge sharing, information quality, IT project management, the perceived usefulness of a BIS, and the perceived ease of adoption of a BIS. This study did not consider the environmental factors’ effect on adopting a BIS (business intelligence system); this is due to the different characteristics of each small and medium enterprise in terms of the sector or industry type.

Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits will not be attained. Currently, there are not enough works to address this problem, and the green status of software products is uncertain and unsure. This paper aims to identify the green measurements based on sustainable dimensions in a software product. The second objective is to reveal the relationships between the elements and measurements through empirical study. The study is conducted in two phases. The first phase is the theoretical phase, where the main components, measurements and practices that influence the sustainability of a software product are identified. The second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achieving green software products. This study has revealed seven green measurements of software product: Productivity, Usability, Cost Reduction, Employee Support, Energy Efficiency, Resource Efficiency and Tool Support. The relationships are statistically significant, with a significance level of less than 0.01 (p = 0.000). Thus, the hypothesised relationships were all accepted. The contributions of this study revolve around the research perspectives of the measurements to attain a green software product.

In the twenty-first century, the use of software is growing due to many applications requiring large and complex software. Many people do not realise that the use of software has influenced the operation of computer hardware to move indirectly as it affects the hardware’s energy consumption and carbon emissions. Previous studies focused more on models and tools to measure the impact of power consumption and energy efficiency from hardware than on software development studies. Energy consumption can be optimised by the greening software process throughout all phases of development activity. Besides, the current green software process models are more focused on environmental and economic elements and do not integrate with the waste elements in the development phase. Integrating sustainability and waste elements is essential to ensure that the development process complies with green process standards. A qualitative method is used through interviews involving eight informants from Malaysia’s public and private sectors. The objectives of the empirical study are to reveal the current practices of the green software process in industry, identify software process waste and determine green factors associated with the software process. The analysis is guided by a thematic approach using Atlas.ti 8 software. This paper describes the results from the qualitative study that consists of three main themes: best practices of a software process, nine software wastes (building the wrong feature, rework, unnecessarily complex solutions, extraneous cognitive load, psychological distress, waiting, knowledge loss, ineffective communication, delay), and six green factors (resources, people, organisational, technical, environmental, technology). The analysis findings indicate that the software industry needs elements of best practices, green practices, and software technologies in each development phase to produce a green and sustainable software process. The advancement of computing today presents technology as an essential factor in green elements to ensure that the software process is constantly updated and always green.

Pollution from quarry activities has a substantial environmental impact on many countries. This issue should be addressed accordingly as its impact may introduce various health-related problems to the surrounding community. One alternative is to increase awareness for the younger generation and society at large. However, environmental data modelling, specifically on quarry activities, has thus far targeted engineers and professionals, not school children, such as for knowledge exploration or learning material. At the same time, the number of students enrolling in STEM courses is continuously declining. Hence, this research aims to develop the environmental virtual interactive based education and learning model called PRInK to foster STEM education. Five components of the proposed model were identified: a) Computer-Assisted Learning; b) Motivation Level; c) Green Environmental Data; d) Learning Outcome; and e) Problem Context. The actual environmental scientific data were used in the simulation and visualisation. Experts in these fields verified the components. The result of the analysis reveals 17 groups of elements, which were further categorised into 58 sub-elements. The model then was validated through prototype development and users validation. The testing and validation of the prototype were carried out on secondary school children, with the results proving the usability and practicality of the model and showed the increased STEM motivation and interest. The PRInK model and the prototype increase society’s awareness about environmental issues starting from school, increase STEM interest and improve the overall quality of life through a shared understanding for future generations.