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Topic Review
Depth Estimation in Structured Driving Scenes
Depth estimation is an important part of the perception system in autonomous driving. Studies often reconstruct dense depth maps from RGB images and sparse depth maps obtained from other sensors. However, existing methods often pay insufficient attention to latent semantic information. Considering the highly structured characteristics of driving scenes, the researchers propose a dual-branch network to predict dense depth maps by fusing radar and RGB images. The driving scene is divided into three parts in the proposed architecture, each predicting a depth map, which is finally merged into one by implementing the fusion strategy in order to make full use of the potential semantic information in the driving scene.
  • 244
  • 22 Sep 2023
Topic Review
Metaverse and AI for Internet of City Things
The Metaverse represents an always-on 3D network of virtual spaces, designed to facilitate social interaction, learning, collaboration, and a wide range of activities. This emerging computing platform originates from the dynamic convergence of Extended Reality (XR), Artificial Intelligence of Things (AIoT), and platform-mediated everyday life experiences in smart cities. However, the research community faces a pressing challenge in addressing the limitations posed by the resource constraints associated with XR-enabled IoT applications within the Internet of City Things (IoCT). Additionally, there is a limited understanding of the synergies between XR and AIoT technologies in the Metaverse and their implications for IoT applications within this framework. 
  • 202
  • 22 Sep 2023
Topic Review
IoMT Based Big Data Framework for COVID-19
The Internet of Medical Things (IoMT) is transforming modern healthcare systems by merging technological, economical, and social opportunities and has recently gained traction in the healthcare domain. The severely contagious respiratory syndrome coronavirus called COVID-19 has emerged as a severe threat to public health. COVID-19 is a highly infectious virus that is spread by person-to-person contact.
  • 252
  • 22 Sep 2023
Topic Review
Algorithms for Facial Expression Recognition in the Wild
Facial expression recognition (FER) in the wild has attracted much attention due to its wide range of applications. Approaches use deep learning models trained on relatively large images, which significantly reduces their accuracy when they have to infer low-resolution images.
  • 239
  • 22 Sep 2023
Topic Review
Smart Healthcare Using ML and Cognitive Radio Technologies
The rapid technological advancements in the modern world bring the attention of researchers to fast and real-time healthcare and monitoring systems. Smart healthcare is one of the best choices for this purpose, in which different on-body and off-body sensors and devices monitor and share patient data with healthcare personnel and hospitals for quick and real-time decisions about patients’ health. Cognitive radio (CR) can be very useful for effective and smart healthcare systems to send and receive patient’s health data by exploiting the primary user’s (PU) spectrum.
  • 537
  • 21 Sep 2023
Topic Review
Leveraging Software-Defined Networking for Named Data Networking
The internet’s future architecture, known as Named Data Networking (NDN), is a creative way to offer content-based services. NDN is more appropriate for content distribution because of its special characteristics, such as naming conventions for packets and methods for in-network caching. Mobility is one of the main study areas for this innovative internet architecture. The software-defined networking (SDN) method, which is employed to provide mobility management in NDN, is one of the feasible strategies. 
  • 223
  • 21 Sep 2023
Topic Review
Machine-Learning Forensics
A world-wide trend has been observed that there is widespread adoption across all fields to embrace smart environments and automation. Smart environments include a wide variety of Internet-of-Things (IoT) devices, so many challenges face conventional digital forensic investigation (DFI) in such environments. These challenges include data heterogeneity, data distribution, and massive amounts of data, which exceed digital forensic (DF) investigators’ human capabilities to deal with all of these challenges within a short period of time.
  • 368
  • 21 Sep 2023
Topic Review
Noise-Tolerant Data Reconstruction for Wireless Sensor Network
Maintaining data dependability within wireless sensor network (WSN) systems has significant importance. Nevertheless, the deployment of systems in unattended and hostile areas poses a major challenge in dealing with noise. Consequently, several investigations have been conducted to address the issue of noise-affected data recovery.
  • 208
  • 21 Sep 2023
Topic Review
Green Energy Transportation Systems on Urban Air Quality
Transitioning to green energy transport systems, notably electric vehicles, is crucial to both combat climate change and enhance urban air quality in developing nations. Urban air quality is pivotal, given its impact on health, necessitating accurate pollutant forecasting and emission reduction strategies to ensure overall well-being. This study forecasts the influence of green energy transport systems on the air quality in Lahore and Islamabad, Pakistan, while noting the projected surge in electric vehicle adoption from less than 1% to 10% within three years. Predicting the impact of this change involves analyzing data before, during, and after the COVID-19 pandemic. The lockdown led to minimal fossil fuel vehicle usage, resembling a green energy transportation scenario. The novelty of this work is twofold. Firstly, remote sensing data from the Sentinel-5P satellite were utilized to predict air quality index (AQI) trends before, during, and after COVID-19. Secondly, deep learning models, including long short-term memory (LSTM) and bidirectional LSTM, and machine learning models, including decision tree and random forest regression, were utilized to forecast the levels of NO22, SO22, and CO in the atmosphere. Our results demonstrate that implementing green energy transportation systems in urban centers of developing countries can enhance air quality by approximately 98%. Notably, the bidirectional LSTM model outperformed others in predicting NO22 and SO22 concentrations, while the LSTM model excelled in forecasting CO concentration. These results offer valuable insights into predicting air pollution levels and guiding green energy policies to mitigate the adverse health effects of air pollution.
  • 150
  • 21 Sep 2023
Topic Review
Analysis-Based ODF Watermarking Algorithm for Edge Cloud Scenarios
With the growing demand for data sharing file formats in financial applications driven by open banking, the use of the OFD (open fixed-layout document) format has become widespread.
  • 269
  • 21 Sep 2023
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