Mobile Phone Network Research Articles

Predicting the impact of public events and mobility in Smart Cities

AbstractThe ubiquitous presence of smartphones and the ever‐expanding Internet of Things are generating a treasure trove of data on human movement. We harness the power of Artificial Intelligence to extract knowledge within this data, in particular for predicting people flows and density in a Smart City. This predictive ability holds immense potential for a multitude of applications, from optimising people flow to streamlining event planning, while offering a powerful tool for pre‐emptive identification of situations that may lead to crowd disasters. In this paper, we tackle two crucial aspects of people mobility using data from public events and an Italian mobile phone network: to predict both event attendance and future crowd density in specific areas. The event details (location, time etc.) are automatically gathered and stored in a structured format. Next, we handle these problems are treated in a “supervised learning” setting, and various state‐of‐art Machine Learning techniques are tested to find the best model for each task. The obtained models will be encapsulated into a Policy Support System contributing to foster planning actions of mobility services.

Received Power Problems in 3G and their Impact on Almadar Aljaded Network Performance

Abstract: In Libya, there are two types of mobile phone networks (Libyana and Almadar Aljaded), and with the development and passage of time, it has become necessary to keep pace with technology smoothly, and on the other hand, the number of network users is increasing, which causes problems that affect the performance of the networks. This study dealt with one of the networks, which is the Almadar Aljaded network for communications and the energy received in the third generation uplink, indicating its values and the factors affecting the studied network, with the development of an algorithm to address the problems that may arise, and this algorithm has proven its effectiveness in addressing three different cases.

Feasibility of hybrid telerehabilitation and telecare in heart failure patients with implanted left ventricular assist device LVAD

Abstract Background Left ventricular assist device (LVAD) implantation is increasingly used as a treatment option for patients with advanced heart failure (HF). There is a need to provide patients with LVAD with long-term care, preferably at home. The implementation of home-based telerehabilitation (HTR) and telecare offers new opportunities in this field. Purpose The purpose of this study was to assess feasibility and safety of HTR and telecare in HF patients with implanted LVAD and evaluate patients’ acceptance of and adherene to HTR. Methods The study enrolled 30 HF patients with recent implanted LVAD (21 Heart Mate III, 9 Heart Ware) (29 males, 19–67, mean 59 years) who underwent a 12-week telecare and HTR program based on walking, respiratory and resistance training, five times weekly. HTR was telemonitored with a device adjusted to register electrocardiogram (ECG) recording and to transmit data via mobile phone network to the monitoring center. The moments of automatic ECG registration were pre-set and coordinated with exercise. The influence on physical capacity was assessed by comparing changes in peak oxygen consumption (VO2 peak; [ml/kg/min]) and workload duration (t; [sec]) in cardiopulmonary exercise test. Results HTR resulted in a significant physical capacity improvement pVO2 12.5±2.9 vs 15.1±3.0 (p<0.001), and workload duration t 628±204 vs 728±222 (p<0.001) in cardiopulmonary exercise test. There were neither deaths nor adverse events during HTR. Patients accepted HTR, including the need for interactive everyday collaboration with the medical team from monitoring center. All patients completed HTR. Conclusions HTR is a feasible, safe form of rehabilitation, well accepted by patients. The adherence to HTCR was high.

Low‐cost animal tracking using Bluetooth low energy beacons on a crowd‐sourced network

Abstract Animal tracking has opened the door to address many fundamental questions in ecology and conservation. Whilst historically animals have been tracked as a means to understand their large‐scale movements, such as migration, there is now a greater focus on using tracking to study movements over smaller scales, individual variation in movement or how movements shape social network structure. With this shift in focus also comes different tracking needs, including the need to track larger numbers of individuals. Tracking studies all face some technological limitations. For example, GPS and other active tracking solutions can collect fine‐scale movement data, but have a high cost per tag, limiting the number of individuals that can be followed. They also have high low‐energy costs of data acquisition and download, limiting time periods over which data can be collected. Low‐energy passive (e.g. PIT) or active (e.g. reverse GPS) tags can overcome these limitations, but instead require animals to remain within a bounded study area or to come into close proximity to detectors. Here we describe one solution that can overcome many current limitations by employing the massive global network of personal mobile phones as gateways for tracking animals using Bluetooth low‐energy (BLE) beacons. In areas with medium to high density of people, these simple‐to‐make beacons can provide regular updates of position over long time periods (battery life 1–3 years). We describe how to use off‐the‐shelf components to produce BLE beacons that weigh c. 5–6 g and cost <$7USD. Using field‐testing, we then show that beacons are capable of producing high‐frequency tracking data that can be used to build home ranges or to detect spatiotemporal co‐occurrences among individuals. BLE beacons are a low cost, low‐energy solution for studying organisms (e.g. birds, mammals and reptiles) living and moving in urban landscapes. Their low weight and small size makes them particularly well‐suited for tracking smaller species. When combined with fixed gateways, their use can also be extended to non‐urban habitats. Their high accessibility is likely to make them an attractive solution for many research projects.

Two Energy-Efficient Backhauling Solutions for Small Cell Networks of 5G Using Green Communications

To meet the problem of ever-increasing wireless data congestion, the fifth-generation (5G) wireless communication system is projected to employ tiny cellphone networks for the needs of consumers heavily. One of the most significant elements of 5G networks will be sustainable interactions, as the quantity of power utilized by the information and communication technology (ICT) sector is expected to rise significantly by the end of the century. Therefore, scientists have focused much attention in recent years on developing strategies for designing small cell networks that use electricity optimistically. In addition, service providers need energy-efficient backing-up technologies to aid in using packed tiny cells. This research presents an interaction model that is well-suited to 5G HetNets and has a low power footprint. The model here accounts for an internet connection’s contact and backup portions. We create and present a mathematical framework to calculate the optimum number of tiny mitochondria that need to be maintained active at numerous hours of the day to minimize power consumption while still satisfying quality of service requirements set by customers. Our investigation into the backhaul’s electrical consumption led us to discover and put forward two energy-saving backing-up methods for 5G HetNets. Computer simulations show that the provided sustainable communication framework can reduce energy consumption by as much as 49% compared to the status quo.

A Mobile Gaming App to Train Teenage Mothers on Appropriate Child Feeding Practices: Development and Validation Study.

Undernutrition is an underlying factor in nearly 50% of 1 million estimated annual deaths among Nigerian children aged <5 years. Inappropriate maternal infant and young child feeding (IYCF) practices are basic contributors to child undernutrition. Teenage motherhood exacerbates the problem of inadequate child feeding. One possible intervention method to improve IYCF knowledge and practices of teenage mothers is the use of mobile gaming technologies. Despite extreme poverty in low- and middle-income countries, a ubiquity of mobile phone networks exists. This study aims to develop and validate a mobile gaming app, called BabyThrive, to train Nigerian teenage mothers on appropriate IYCF practices. To identify gaps in current IYCF practices in northern Nigeria, we conducted an extensive search of the literature and held 2 focus group interviews with 16 teenage mothers with low-income status. An initial app content design was then created, and content validity was established by 10 nutrition experts. Next, we developed an app prototype, which was assessed for quality by 7 nutrition and mobile gaming experts and evaluated for usability by 90 teenage mothers from rural areas in Abuja, the country's capital. The final app, BabyThrive, is a 2D mobile game that is fully functional offline and available in English as well as Hausa, which is commonly spoken in northern Nigeria. The efficacy of the BabyThrive app was assessed using IYCF knowledge scores obtained from the administration of the validated Teen Moms Child Feeding Questionnaire for Sub-Saharan Africa. Construct validity was established via crossover design by comparing the total IYCF knowledge scores of the teenage mothers obtained after a verbal training program and BabyThrive app use. Large proportions of the study participants were married (53/90, 59%) and had no personal income (63/90, 70%). The mean quality rating for the BabyThrive app was 4.3 (SD 0.39) out of 5.0. High levels (>80%) of usability and user satisfaction were documented. Knowledge of exclusive breastfeeding (P<.001) and total knowledge scores (P=.002) were significantly higher in the BabyThrive group than in the verbal training group. The IYCF knowledge scores obtained from both groups showed coherence, with a statistically significant Spearman correlation coefficient of 0.50 (P<.001). This research developed and validated a novel, offline mobile gaming app. It will be an easy, effective, and acceptable method to disseminate critical knowledge on IYCF practices to teenage mothers in rural Nigeria.

Determining the relationship between mobile phone network signal strength and radiofrequency electromagnetic field exposure: protocol and pilot study to derive conversion functions

Mobile phones continuously monitor and evaluate indicators of the received signal strengths from surrounding base stations to optimise wireless services. These signal strength indicators (SSIs) offer the potential for assessing radiofrequency electromagnetic field (RF-EMF) exposure on a population scale, as they can be related to exposure from both base stations and handset devices. Within the ETAIN (Exposure To electromAgnetic fields and plaNetary health) project, an open-access RF-EMF exposure app for smartphones, named "5G Scientist Monitor”, has been developed using citizen science. This paper delineates a measurement protocol for deriving formulas to convert the app SSIs into electric field values to estimate RF-EMF exposure. It presents pilot study results from measurements taken at four locations in Lyon, France (FR), and 14 locations in the Netherlands (NL), using three different phone models and the most common network providers in each country. The measurements were conducted while executing different usage scenarios, such as calls or data transmission. The exposimeter ExpoM-RF4 and on-body electric field probes were used to measure exposure from far-field sources and the handset, respectively. Two-minute aggregates were considered the sample unit for analyses (n=891 in NL and n=395 in FR). Regression analyses showed a positive log-linear relationship between Long Term Evolution (LTE) SSIs and far-field RF-EMF exposure when aggregating data by location (coefficients for the normalised RSSI: 0.91 [95% CI: 0.55 - 1.28] in FR, 1.09 [95% CI: 0.96 - 1.22] in NL). Negative log-linear trends were observed for handset-related RF-EMF exposure at the ear (-0.31 [95% CI: -0.46 - -0.16]) and chest (-0.20 [95% CI: -0.37 - -0.03]) during data transmission scenarios. These results demonstrate that the 5G-Scientist-Monitor app can be implemented for smartphone-based RF-EMF estimation. However, uncertainties in individual measurement points highlight the need for further data collection and analysis to improve the accuracy of exposure estimates.

Factors Affecting for Using Services of Mobile Phone Network for Customer of the Lao Telecommunications Company, Oudomxay Province

The purpose of this study was1) to study the situationof customers using mobile phone network services of Lao Telecommunications Company, 2) to studythe significantbetween customers andthe mobile network of Lao Telecommunications Company, 3) to findout the factors affecting customer's loyalty to the mobile phone network service of Lao Telecommunication Public Company.It was a quantitative research with the target group being customers who use the service through the mobile phone network of customers of Lao Telecommunications Company in Uodomxay province, used402 sample group and questionnaires were usedto collect data and analyzedthe data by usingSPSS program. The results found that most of the users of the Lao Telephony network service wereusing the Internet (Data), spending 50,000-100,000 kip per month, the period of using the number is more than 2 years. The important aspects in makinga relationship with Lao Telecom customers are marketing promotion, service process, customer monitoring, administration, communication between customers, and partnership which are in the high level. Factors affecting customers' loyalty to Lao Telecommunication Public Company's mobile network services include repeat service use factors, referral factors, and non-switching network factors with a statistical significancelevel of 0.01

Mobile Technology for Farmers: An Overview of Agricultural Apps

A growing trend in agriculture is the use of mobile applications or apps on smartphones. Through the apps, farmers may obtain all information and answers with a single tap. Information about pests and diseases, scheme-related facts and the specifics of the package of practices are all kept in mobile devices for convenient access. Small-scale farmers make up the bulk of Indian farmers. They frequently lack access to the technological and informational resources that could help them raise the productivity of their crops and products and obtain higher prices. The ubiquitous mobile phone network provided a solution to this issue. The majority of apps are only useful for a certain amount of information, while some have multiple uses. This study examines the mobile applications for agriculture that are accessible in India and are intended for farmers. It is more likely that mobile apps in the agricultural and related industries will become more integrated and dependent. In the present study the Plantix application more effective as it is informative, simple and easy to use app.

Research on Mobile Network Parameters Using Unmanned Aerial Vehicles.

The study of phenomena related to the propagation of electromagnetic waves is a necessity with the development of mobile telephony networks. This paper deals with the problem of the quality of mobile telephony signals. The study uses a BTS scanner, dedicated to scanning the frequency spectrum and decoding information from base stations. The device is capable of scanning mobile networks from the second, third, fourth, and fifth generation (2G/3G/4G/5G) using a passive sensor. The article presents preliminary results of monitoring cellular network signals using a scanner mounted on an unmanned aircraft. The collected data call for the need to evaluate the signal parameters of the cellular network depending on the altitude of signal reception. This property emerges as very important in the case of areas with a high level of urbanization.

Man versus machine: cost and carbon emission savings of 4G-connected Artificial Intelligence technology for classifying species in camera trap images

Timely and accurate detection and identification of species are crucial for monitoring wildlife for conservation and management. Technological advances, including connectivity of camera traps to mobile phone networks and artificial intelligence (AI) algorithms for automated species identification, can potentially improve the timeliness and accuracy of species detection and identification. Adoption of this new technology, however, is often seen as cost-prohibitive as it has been difficult to calculate the cost savings or qualitative benefits over the life of the program. We developed a decision tool to quantify potential cost savings associated with incorporating the use of mobile phone network connectivity and AI technologies into monitoring programs. Using a feral cat eradication program as a case study, we used our decision tool to quantify technology-related savings in costs and carbon emissions, and compared the accuracy of AI species identification to that of experienced human observers. Over the life of the program, AI technology yielded cost savings of $0.27 M and when coupled with mobile phone network connectivity, AI saved $2.15 M and 115,838 kg in carbon emissions, with AI algorithms outperforming human observers in both speed and accuracy. Our case study demonstrates how advanced technologies can improve accuracy and cost-effectiveness and improve monitoring program efficiencies.

Assessing tourism impact on cultural landscapes using mobile phone data: the case of Las Médulas (Spain).

Cultural landscapes often pose problems for planning and management because of insufficient information regarding visitor movements, interests and infrastructure burden. Traditionally visitor surveys have helped to fill this gap, albeit limited to their incomplete and occasional nature. This paper presents a methodology for using cellular antenna metadata for understanding tourism flows. This information is collected systematically by the mobile phone network but only recently has its big data potential begun to be exploited for understanding socio-economic phenomena. The present case study of the Roman gold mine of Las Médulas (León, Spain) provides a model for tourism impact analysis using anonymized data from cell phone towers.

Digital opportunities for the distribution of index‐based microinsurance: Evidence from a discrete choice experiment in Mali

AbstractIndex‐based microinsurance is a promising risk management tool for smallholder farmers. Recently, several mobile‐delivered insurance schemes have entered the market. Depending on the degree of digitisation of the product, farmers can learn about the insurance, register, pay premiums and receive payouts via a mobile phone. As cell phone usage and network coverage constantly increase, digitally enabled insurance distribution may overcome previous barriers for insurance adoption. Still, farmers' preferences for these products remain largely unknown. We address this knowledge gap by means of a discrete choice experiment applied to 499 maize farmers in Mali. The experiment presents an easy‐to‐understand multi‐peril crop insurance linked to a greenness index. It focuses on attributes related to the distribution channel and product design. Using mixed logit models, we find that the insurance attributes enabled by mobile‐delivery are attractive to farmers. Product bundles that include mobile‐delivered weather information and agricultural advice in addition to the insurance policy or credit access increase the likelihood of farmers taking out insurance. Similarly, recommendations from fellow farmers increase interest in the insurance product. The results are highly relevant for future product improvements that are needed to increase adoption rates and ultimately realise the loss‐hedging potential of microinsurance.

Spatial Variation of the Received Signal Strength of Mobile Telephone Network (MTN) over Dutsin-Ma Town, Katsina State, Nigeria

The need for coverage areas assessment is important at ensuring quality of service. This study investigated the spatial variation of the Received Signal Strength (RSS) of MTN in Dutsin-Ma Town, Katsina State, Nigeria. The RSS was measured along four different routes from the main Transmitting Base Station (TBS) located at Unity Bank area using an Android Smartphone Samsung Galaxy Model A20. GPS receiver was used to monitor the elevation, geographic coordinates and Line-of-Sight of the various data points from the TBS up to about 2 km for each route using drive test protocol. Three sets of measurements were carried out covering morning, afternoon and evening. The obtained data were used to classify the coverage areas into Primary, Secondary, Tertiary and Fringe based on 3/4G-GSM standards. From the results, the mean values of the RSS for Routes A, B, C and D were -62, -91 and -75 dBm; -71, -90 and -85 dBm; -68, -99 and -83 dBm; -63, -93 and -83 dBm for morning, afternoon and evening respectively. These findings revealed that MTN RSS is more reliable in the morning and evening compared to the afternoon over Dutsin-Ma. This could be attributed to higher tower load which characterizes the afternoon times compared to morning and evening. Results also revealed that Route A, has the Best Area Network coverage, followed by routes D and B, while route C recorded the weakest. MTN Nigeria is advised to site more TBS in Dutsin-Ma to improve their quality of services in the community.

POSITION BASED ROUTING USING INTERNET CONTACT TO VANET THROUGH SATELLITE RECEIVE-ONLY TERMINAL

The most challenging barrier to expanding connectivity of Internet to vehicle ad hoc networks is the necessity for vast proper infrastructure of roadside network. This need is problematic to meet, specifically in the early stages of vehicle network building &amp; in zones with limited infrastructure of roadside. As a result, that solutions rely exclusively on roadside structure are unworkable. Other remedies, like cell phone networks / symmetrical communications via satellite, are also too expensive or do not deliver adequate connectivity, putting the change to a robust VANET difficulty in the later stages. We provide one method that supplements obtainable ones while avoiding the need for completely networked roadside infrastructure. To provide widespread Internet access, the approach employs satellite receive-only endpoints and a small number of (widely dispersed) wayside devices. The solution is affordable, gradual, and practical. We show numerous design possibilities that can be employed depending on the environment.

Design a hybrid meta-heuristic algorithm for optimal multicell-MMSE to maximize the spectral efficiency in massive MIMO systems

Abstract Due to many capabilities, “massive multiple-input multiple-output (MIMO) systems” are regarded as a crucial enabling innovation. High energy economy, great spectral efficiency (SE), and simultaneous communication to many user equipments (UEs) are some of the sophisticated characteristics of massive MIMO systems. Huge MIMO, which involves installing arrays of antennas with a high amount of active components at the base station (BS) and utilizing coherent baseband processing, is a viable method for boosting the SE of cell phone networks. Massive MIMO’s spatial multiplexing and unparalleled array gain can increase the processing power of cellular networks. Since its origin, it has been assumed that when the number of radios increases infinitely, the coherent interference brought on by pilot emissions leads to a limited capacity limit. To achieve this objective, an optimal multicell MMSE is proposed for SE maximization. It is processed as the precoding or combining technique that is considered the small amount of spatial channel correlation, more capacity and more number of antennas, large-scale fading variations, and pilot contamination. It is noted that several cases for increasing the SE, thus it contain multiple antenna information. The prime novelty of this paper is introducing the hybrid heuristic algorithm, named as Fitness-condition of red deer and rat swarm algorithm (FRDRSA) for providing the best solution. Finally, the work performance that produced the extensive findings is examined. On the other hand, the suggested method produces an impressive result when measuring the system’s overall SE.

Service contract type and consumer choice behavior: the contributory roles of perceived value, brand reputation and consumer incentives

PurposeTo minimize customer churn, many service providers offer consumers the option of automatic contract renewal at the end of a contract period. Such agreements are known as rollover service contracts (RSCs). This research quantifies the effect of RSCs and other related factors, such as incentives, on consumers' service choice decisions.Design/methodology/approachThe study adopts choice-based conjoint analysis to assess the effect of RSCs on consumers' choices and to determine whether effect size varies when selecting a cell phone network or gym/leisure club provider, which represent lower-priced utilitarian and higher-priced hedonic services.FindingsIt was found that RSCs produce negative perceptions and intended behaviors for the majority of consumers across different product types. Nevertheless, as explained by social exchange theory, many individuals may be persuaded to enter into a RSC on the basis of reciprocity if they are offered an incentive such as a price discount or free product add-on.Originality/valueIn the marketing domain, this is the first comprehensive study to quantify the role of contract type among a range of other factors in consumers' decision-making when selecting a service. The authors' results offer context-specific implications for service marketers. First, RSCs are perceived more negatively in high-priced hedonistic categories, especially among those with lower incomes. Second, price discounts are more effective than product add-ons for motivating hedonic purchases, while product add-ons work better with utilitarian services.

Early detection of critical urban events using mobile phone network data.

Network Signalling Data (NSD) have the potential to provide continuous spatio-temporal information about the presence, mobility, and usage patterns of cell phone services by individuals. Such information is invaluable for monitoring large urban areas and supporting the implementation of decision-making services. When analyzed in real time, NSD can enable the early detection of critical urban events, including fires, large accidents, stampedes, terrorist attacks, and sports and leisure gatherings, especially if these events significantly impact mobile phone network activity in the affected areas. This paper presents empirical evidence that advanced NSD can detect anomalies in mobile traffic service consumption, attributable to critical urban events, with fine spatial (a spatial resolution of a few decameters) and temporal (minutes) resolutions. We introduce two methodologies for real-time anomaly detection from multivariate time series extracted from large-scale NSD, utilizing a range of algorithms adapted from the state-of-the-art in unsupervised machine learning techniques for anomaly detection. Our research includes a comprehensive quantitative evaluation of these algorithms on a large-scale dataset of NSD service consumption for the Paris region. The evaluation uses an original dataset of documented critical or unusual urban events. This dataset has been built as a ground truth basis for assessing the algorithms' performance. The obtained results demonstrate that our framework can detect unusual events almost instantaneously and locate the affected areas with high precision, largely outperforming random classifiers. This efficiency and effectiveness underline the potential of NSD-based anomaly detection in significantly enhancing emergency response strategies and urban planning. By offering a proactive approach to managing urban safety and resilience, our findings highlight the transformative potential of leveraging NSD for anomaly detection in urban environments.

From 'Mobile' to 'Really Mobile': Mobile phones in Scandinavian Advertisements from the 1980s

Mobile phones represent a new era in telecommunications beginning in the 1980s with the development of first-generation mobile phone networks. This article addresses the early history of the mobile phone from a cultural and aesthetic perspective with focus on representations of mobile phones in advertising. The aim is to explore whether images of early mobile phones as trendy and stylish artefacts suggested by examples in a previous study by the author represent a more common aesthetic trend related to advertising and consumer culture in the 1980s. The study is based on a sample of Scandinavian advertisements from 1980 to 1989.

Actionable descriptors of spatiotemporal urban dynamics from large-scale mobile data: A case study in Lisbon city

Mobile phones share location records, offering the opportunity to monitor and understand emerging population dynamics in urban centers. With the aim of supporting urban planning, this study introduces a scalable methodology grounded on extracting and organizing spatiotemporal statistics from decomposed population density data. The proposed methodology serves three major purposes: (i) assess the predictability of spatiotemporal citizen density patterns; (ii) detect emerging spatiotemporal trends in population density; and (iii) uncover multi-level seasonality patterns with guarantees of actionability. Additionally, it makes available an open-access tool for deploying the proposed methodology and analyzing mobile phone network data with easy-to-use spatiotemporal visualization and navigation facilities. The results obtained from real-world, large-scale mobile data in Lisbon, Portugal, demonstrate the effectiveness and validity of the proposed methodology in extracting actionable statistics in linear time to guide both tactic and strategic urban planning.