Journal of Mobile Multimedia

Editorial: Special Issue on “Massive Information by a Plethora of Devices (AIMS)”

2025-02-07T04:28:02+01:00

The 26th Edition of Strategic Workshop (SW’23) was held on October 25–27, 2023 in Croatia. During the active 3-day discussion, the workshop centred on the theme “Massive Information by a Plethora of Devices (AIMS),”, presenting the concept, intelligent discoveries, digital technology-oriented business models, proposals for sustainability solutions & global partnership. The Workshop also discussed the challenges and opportunities arising from the vast amounts of data generated by the proliferation of connected devices in today’s interconnected world and the project proposal talks in the relevant area.

Downlink Power Allocation with Stackelberg Game in NOMA System

2024-03-14T15:53:15+01:00

Non-Orthogonal Multiple Access (NOMA) is regarded as one of the most promising technologies for the fifth generation (5G) mobile communications. This paper delves into the NOMA downlink power allocation under the introduction of a Stackelberg game with uniform pricing and discounted pricing strategies, specifically addressing scenarios involving imperfect successive interference cancellation (SIC). The Stackelberg game is commonly employed to characterize strategic interactions, inherently involving a leader and followers. In this paper, the base station plays the role of the leader, making decisions regarding the price charged to the followers. On the other hand, users take on the role of followers, deciding the quantity of power to purchase. In each round of the game, driven by the pursuit of maximizing their respective utility functions, both roles iteratively adjust their strategies based on the decisions proposed by the other party until reaching the Stackelberg Equilibrium. Through the simulations, we compare the power allocated to the users and the obtained achievable rates under different scenarios, including imperfect SIC with uniform (ISIC-U) pricing strategy, imperfect SIC with discounted (ISIC-D) pricing strategy, and perfect SIC (PSIC). Simulation results reveal that the proposed ISIC-U and ISIC-D can obtain better power saving and fairness among achievable rates, while only sacrifice quite limited total achievable rate.

Leveraging Massive Information from Diverse Devices: An Intelligent, Low-Cost, Voice-Controlled Autonomous Wheelchair for Enhanced Mobility

2024-05-30T10:12:46+02:00

This paper explores the development of an intelligent, low-cost, voice-controlled autonomous wheelchair designed to enhance mobility for individuals with disabilities. The wheelchair integrates diverse data from multiple devices, including a voice recognition module, joystick module, ultrasonic sensors, and solar panels, to provide a comprehensive and adaptive user experience. Leveraging massive information from these interconnected devices, the wheelchair employs artificial intelligence and machine learning algorithms to refine its responsiveness to users’ voice commands, improving adaptability to individual speech patterns over time. The solar panels contribute to the wheelchair’s sustainability by harnessing solar energy for battery charging, ensuring prolonged operation without frequent recharging. This study details the design methodology, fabrication process, and performance testing of the wheelchair, showcasing its capabilities such as an optimum speed of 0.89 m/s, a load capacity of 20 kg, and effective obstacle avoidance. Additionally, the paper addresses the wheelchair’s advantages, potential limitations, and future enhancements. By leveraging diverse data sources and intelligent systems, this innovative wheelchair aims to significantly improve mobility, individuality, and worth of life for beings with mobility challenges and the elderly.

Cultural Heritage Monitoring and Predictive Maintenance using Internet of Things: Assessment and Future Aspects

2024-06-02T18:11:03+02:00

This study presents a detailed survey on the use of the Internet of Things (IoT) for predictive maintenance and monitoring of cultural heritage, focusing on museums and exhibitions. The integration of IoT in these fields offers significant potential for optimizing maintenance and supervision of heritage resources while also enhancing maintenance strategies. This review examines the application of IoT devices, data analysis, and predictive algorithms in monitoring the state of heritage resources to improve tourist experiences and conserve cultural resources. Key enabling technologies can enable adaptive interactions and engagement with enhanced navigation. Visualization technologies are also common, offering hands-on displays. The study also emphasizes the value of accessibility and interactivity, providing personalization and content sharing features. Several initiatives prioritize the delivery of digital content through mobile applications, internet browsers, and downloadable resources.This study examines how IoT-enabled predictive maintenance systems can recognize potential hazards, like resource decay or environmental dangers, enabling immediate action. This survey also highlights trends, challenges, and future research in IoT and cultural heritage monitoring.

Models Prediction and Estimation of ENSO and Karachi Rainfall Cycles Through AR-GARCH and GARCH Process

2024-03-29T18:31:45+01:00

Karachi rainfall and ENSO cycles have influenced on earth climates. The effects of El-Nino Southern Oscillation (ENSO) on the rainfall climate system of the Karachi region are analyzed. The research is working on the ENSO and rainfall Karachi region massive datasets information gathered for the period 1961–2021, which are break down into cycles (1st – 10th). The novelty of this study is to analyze the factor of the ENSO effect, which is parallel to the Karachi rainfall region, as well as other factors such as deforestation. ENSO-Rainfall Karachi region cycles are also measured via statistical techniques. The estimate Model and forecasting of volatility through the comparative study of AR(R) – GARCH (P, Q) and GARCH (P, Q) Models. Effect of El Niño-Southern Oscillation (ENSO) on Karachi Rainfall as a case study suitable to research on its behavior for estimating forecast evolution of ENSO-Rainfall Karachi region cycles. The technique of AR(R) – GARCH (P, Q) and GARCH (P, Q) process is feasible for ensuring the appropriateness of the impacts on Karachi region rainfall and ENSO cycle. Different value of AR(R) – GARCH (P, Q) and GARCH (P, Q) Models is used. RMSE, MAE, MAPE and U Test are calculated to describe which technique provide the maximum accuracy of forecasting and Predictions. Most of the forecasting evaluation describe that GARCH (P, Q) has highest accuracy to predicting and forecasting ENSO and Karachi Rainfall Cycles as comparative others three models. This study confirms that, the duration of ENSO years, the tendency of Karachi region rainfall is reduced. The study shows that the relationship between ENSO-Rainfall Karachi region cycles are uncertainty. In the immediate year following the El Nino event, the July and September months, as well as the summer monsoon season, had a statistically significant 90% rainfall deficit.

Forecasting Karachi’s Air Temperature Variation: Leveraging Mobile and Multimedia Dataset for Global Warming Insights

2024-03-31T15:03:45+02:00

In Karachi, the transport and building industries have a major impact on carbon dioxide (CO2) emissions and greenhouse gas emissions. This study is innovative in that it examines how air temperature changes over time and forecasts the maximum and minimum temperatures in Karachi. Specifically, it looks at 60 years’ worth of mean monthly maximum and minimum air temperatures in Karachi, spanning from (1961 to 2020) dataset classes. The monthly average air temperature in Karachi, both at its minimum and maximum, remains constant. Using dataset from the Pakistan Metrological Department (PMD) and, the ARMA (p, q) model technique was used to assess forecasting and modelling the behavior of the maximum and minimum air temperatures in Karachi. The least values Akaike information criterion (AIC), the Bayesian Schwarz information criterion (SIC), and the Hannan Quinn information criterion (HIC) are used to describe how adequate the model is. Additionally, the Durbin-Watson (DW) test is used. The average monthly maximum and minimum air temperature in Karachi are strongly correlated, as indicated by DW values (<2). The lowest and maximum monthly average air temperatures in Karachi are predicted using diagnostic checking techniques such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Theil’s U-Statistics. The results indicate that there is a strong correlation between the air temperature and previously measured values, with Theil’s U-Statistics values for each month lying close to zero. This study is a great resource for observing how air temperature affects global warming. This study also highlights the the innovative aspect of utilizing vast datasets, possibly including those from mobile and multimedia sources, to address a critical environmental issue. It also emphasizes the predictive modelling aspect of your study, which is central to understanding and mitigating global warming effects.

Massively Flexible Mobile Systems

2024-03-19T19:34:07+01:00

5G network is expected to provide mMTC (massive Machine Type Communications or massive Internet of Things [mIoT]) slices in the near future, coinciding with expectations for a significant increase in the IoT global market. Many new IoT use cases are anticipated to be deployed using 5G which requires mMTC performance. Release 17 introduces several mMTC features. However, as of release 19, 3GPP does not claim full support of mMTC slices.

Even if 5G cannot fully support mMTC network slices yet, several network features are already standardized and included in commercial-graded 5G networks. These features allow for the reconfiguration of the network to provide communication performance close to what is provided in mMTC slices. This paper analyzes and evaluates several of these features, demonstrating that current 5G networks are already capable of supporting some of the mMTC use cases expected to be deployed in the future.