The Role of 5G Technologies in a Smart City: The Case for Intelligent Transportation System

The interaction between remittance, FDI, renewable energy, and environmental quality: a panel data analysis for the top remittance-receiving countries

A country's financing system is essential in addressing sustainable development requirements. National sources and international financial flows contribute to economic growth and environmental quality in many ways, and their impact can be critical. This paper applied panel data analysis using a comparative approach of Pooled Mean Group Auto Regressive Distribute Lags (PMG-ARDL) and Cross Sectionally ARDL (CS-ARDL) to estimate the effects of FDI, renewable energy, and remittance on environmental quality in the top remittance-receiving countries, during 2000-2021. The study emphasized the positive relationship between FDI and carbon emissions. Moreover, renewable energy and remittances revealed an inverted U-shaped relationship with carbon emissions. In the case of developing countries from the panel, remittance improves environmental quality after reaching the threshold. Moreover, for some of the developing countries included in the panel, we found that they do not achieve the desired carbon mitigation effect in their early stages of renewable energy implementation. However, renewable energy becomes a key factor for tackling environmental pollution after a certain threshold. The mixed results determined diverse policy recommendations for various stakeholders.

Exploring the Risks, Benefits, Advances, and Challenges in Internet Integration in Medicine With the Advent of 5G Technology: A Comprehensive Review

The integration of 5G technology in the healthcare sector is poised to bring about transformative changes, offering numerous advantages such as enhanced telemedicine services, expedited data transfer for medical records, improved remote surgery capabilities, real-time monitoring and diagnostics, advancements in wearable medical devices, and the potential for precision medicine. However, this technological shift is not without its concerns, including potential health implications related to 5G radiation exposure, heightened cybersecurity risks for medical devices and data systems, potential system failures due to technology dependence, and privacy issues linked to data breaches in healthcare. We are striking a balance between harnessing these benefits and addressing the associated risks. Achieving this equilibrium requires the establishment of a robust regulatory framework, ongoing research into the health impacts of 5G radiation, the implementation of stringent cybersecurity measures, education and training for healthcare professionals, and the development of ethical standards. The future of 5G in the medical field holds immense promise, but success depends on our ability to navigate this evolving landscape while prioritizing patient safety, privacy, and ethical practice.

Editorial for the Special Issue on the New Trends in Microwave/Millimeter Antennas/Filters: From Fundamental Research to Applications

The rapid growth of wireless communication systems has led to high demand for the design of microwave/millimeter components with multiband characteristics, high performance, and ease of integration with other devices [...].

6G-Enabling the New Smart City: A Survey

Smart cities and 6G are technological areas that have the potential to transform the way we live and work in the years to come. Until this transformation comes into place, there is the need, underlined by research and market studies, for a critical reassessment of the entire wireless communication sector for smart cities, which should include the IoT infrastructure, economic factors that could improve their adoption rate, and strategies that enable smart city operations. Therefore, from a technical point of view, a series of stringent issues, such as interoperability, data privacy, security, the digital divide, and implementation issues have to be addressed. Notably, to concentrate the scrutiny on smart cities and the forthcoming influence of 6G, the groundwork laid by the current 5G, with its multifaceted role and inherent limitations within the domain of smart cities, is embraced as a foundational standpoint. This examination culminates in a panoramic exposition, extending beyond the mere delineation of the 6G standard toward the unveiling of the extensive gamut of potential applications that this emergent standard promises to introduce to the smart cities arena. This paper provides an update on the SC ecosystem around the novel paradigm of 6G, aggregating a series of enabling technologies accompanied by the descriptions of their roles and specific employment schemes.

Smart Transportation: An Overview of Technologies and Applications

As technology continues to evolve, our society is becoming enriched with more intelligent devices that help us perform our daily activities more efficiently and effectively. One of the most significant technological advancements of our time is the Internet of Things (IoT), which interconnects various smart devices (such as smart mobiles, intelligent refrigerators, smartwatches, smart fire alarms, smart door locks, and many more) allowing them to communicate with each other and exchange data seamlessly. We now use IoT technology to carry out our daily activities, for example, transportation. In particular, the field of smart transportation has intrigued researchers due to its potential to revolutionize the way we move people and goods. IoT provides drivers in a smart city with many benefits, including traffic management, improved logistics, efficient parking systems, and enhanced safety measures. Smart transportation is the integration of all these benefits into applications for transportation systems. However, as a way of further improving the benefits provided by smart transportation, other technologies have been explored, such as machine learning, big data, and distributed ledgers. Some examples of their application are the optimization of routes, parking, street lighting, accident prevention, detection of abnormal traffic conditions, and maintenance of roads. In this paper, we aim to provide a detailed understanding of the developments in the applications mentioned earlier and examine current researches that base their applications on these sectors. We aim to conduct a self-contained review of the different technologies used in smart transportation today and their respective challenges. Our methodology encompassed identifying and screening articles on smart transportation technologies and its applications. To identify articles addressing our topic of review, we searched for articles in the four significant databases: IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Consequently, we examined the communication mechanisms, architectures, and frameworks that enable these smart transportation applications and systems. We also explored the communication protocols enabling smart transportation, including Wi-Fi, Bluetooth, and cellular networks, and how they contribute to seamless data exchange. We delved into the different architectures and frameworks used in smart transportation, including cloud computing, edge computing, and fog computing. Lastly, we outlined current challenges in the smart transportation field and suggested potential future research directions. We will examine data privacy and security issues, network scalability, and interoperability between different IoT devices.

RF Coverage Design for the Implementation of a Broadband Monitoring Service in the Context of 5G-Enabled Smart Cities

As the recent COVID-19 pandemic has aptly demonstrated, emergency scenarios concerning public health and safety may require citizens to remain at home even as patients, potentially in the context of a municipal or national lockdown. Homestay patients may require real-time monitoring, which will offer not only communication but also empirical data and will contribute to developing their personalized electronic health record in knowledge bases. Our paper features an extensive RF coverage design for such a municipally deployed and administered 5G-enabled smart city network, supporting a broadband monitoring service. The antenna deployment for the outdoor urban topology is analytically described (for the downlink channel), and the intrinsic indoor propagation characteristics are considered for the uplink channel. A digital baseband signaling scheme is assumed on the basis of a user-customized health-related monitoring service. Path loss and fading calculations consider the potential worst-case propagation conditions so that the RF coverage will be reliable, leading to a resilient city-wide municipal network.

Near Field Models of Spatially-Fed Planar Arrays and Their Application to Multi-Frequency Direct Layout Optimization for mm-Wave 5G New Radio Indoor Network Coverage

Two near field models for the analysis of spatially fed planar array antennas are presented, compared and applied to a multi-frequency wideband direct layout optimization for mm-Wave 5G new radio (NR) indoor network coverage. One model is based on the direct application of the radiation equations directly derived from the A and F vector potentials. The second model is based on the superposition of far field contributions of all array elements, which are modelled as rectangular apertures with constant field. Despite the different assumptions made to develop both models, the degree of agreement between them in the computation of the radiated near field is very high. The relative error between the models is equal or lower than 3.2% at a plane 13λ from the array, and it decreases as the near field is computed further away from the array. Then, the faster model is employed in a general direct layout optimization procedure to shape the electromagnetic near field for application in an indoor femtocell to provide coverage with constant power in a private office. Results show that a magnitude ripple better than 1.5 dB can be achieved in an enlarged coverage area covering the whole n257 band of the 5G NR, corresponding to a 10.7% relative bandwidth.

Novel Fuzzy Logic Scheme for Push-Based Critical Data Broadcast Mitigation in VNDN

Vehicular Named Data Networking (VNDN) is one of the potential and future networking architectures that allow Connected and Autonomous Vehicles (CAV) to exchange data by simply disseminating the content over the network. VNDN only supports a pull-based data forwarding model, where the content information is forwarded upon request. However, in critical situations, it is essential to design a push-based data forwarding model in order to broadcast the critical data packets without any requests. One of the challenges of push-based data forwarding in VNDN is the broadcasting effect, which occurs when every vehicle broadcasts critical information over the network. For instance, in emergency situations such as accidents, road hazards, and bad weather conditions, the producer generates a critical data packet and broadcasts it to all the nearby vehicles. Subsequently, all vehicles broadcast the same critical data packet to each other, which leads to a broadcast storm on the network. Therefore, this paper proposes a Fuzzy Logic-based Push Data Forwarding (FLPDF) scheme to mitigate the broadcast storm effect. The novelty of this paper is the suggestion and application of a fuzzy logic approach to mitigate the critical data broadcast storm effect in VNDN. In the proposed scheme, vehicles are grouped into clusters using the K-means clustering algorithm, and then Cluster Heads (CHs) are selected using a fuzzy logic approach. A CH is uniquely responsible for broadcasting the critical data packets to all other vehicles in a cluster. A Gateway (GW) has the role of forwarding the critical data packets to the nearest clusters via their GWs. The simulation results show that the proposed scheme outperforms the naive method in terms of transmitted data packets and efficiency. The proposed scheme generates five times fewer data packets and achieves six times higher efficiency than the naive scheme.

Research on Location Selection Model of 5G Micro Base Station Based on Smart Street Lighting System

In order to promote the development and construction of smart cities, the massive equipment requirements of sensing terminals increased the pressure on urban site resource allocation. The light pole is suitable for carrying various urban functional equipment to form a smart street lighting system, which can provide rich site resources for the large-scale construction of urban functional facilities such as 5G micro base stations. However, the selection and combination of equipment mounted in the smart street lighting system only focus on the functional superposition at the physical level, without considering the relevance of each subsystem in practical application scenarios. Therefore, this study proposed a 5G micro base station location model based on a smart street lighting system. The correlation and cooperativity between 5G micro base stations and mounted devices were fully considered, and a universal system-level location selection index was developed to realize rational utilization of urban space site resources and intelligent linkage between subsystems. The results showed that the model is significantly effective for functional areas with different road network characteristics and provides practical, robust, effective, and accurate help for similar location selection problems.

How to Promote Urban Intelligent Transportation: A Fuzzy Cognitive Map Study

As an important part of smart city, intelligent transportation is an critical breakthrough to solve urban traffic congestion, build an integrated transportation system, realize the intelligence of traffic infrastructure and promote sustainable development of traffic. In order to investigate the construction of intelligent transportation in cities, 20 initial affecting variables were determined in this study based on literature analysis. A questionnaire collected from professionals in intelligent transportation was conducted, and a total of 188 valid responses were received. Then the potential grouping was revealed through exploratory factor analysis. Finally, a causal model containing seven concepts was established using the practical experience and knowledge of the experts. A root cause analysis method based on fuzzy cognitive map (FCM) was also proposed to simulate intelligent transportation construction (ITC). The results indicate:(1) The 20 variables can be divided into six dimensions: policy support (PS), traffic sector control (TSC), technical support (TS), communication foundation (CF), residents’ recognition (RR), and talent quality (TQ); and (2) In the FCM model, all six concept nodes (PS, TSC, TS, CF, RR, and TQ) have a significant positive correlation with the target concept node ITC. The rank of the six dimensions according to correlation strength is TS, CF, PS, TSC, RR, and TQ. The findings of this paper can help academics and practitioners understand the deep-seated determinants of urban intelligent transportation construction more comprehensively, and provide valuable suggestions for policy makers. And thus, the efficiency of intelligent transportation construction can be improved.

A Multi-Criteria Evaluation of Applications Supporting Public Transport Users

Reducing the energy consumption of transport in urban areas is possible if appropriate measures are taken to make public transport more attractive. These include all kinds of journey planners that are part of the passenger information system. Various applications available on the market allow passengers to evaluate their usability. This paper presents and compares nine of the most popular journey planners available to iOS and Android users travelling in Krakow. The comparison took into account all the information obtained from the surveys. In addition, using a multi-criteria approach, the final ranking of the set of journey planners was developed. The assessment was made on the basis of a set of nine criteria indicated by travellers as the most important ones. The obtained results showed disproportions in the functionality of particular solutions. They also indicated the apps that are most frequently and willingly used by local (urban city/agglomeration) travellers.

A Cyber-Physical Approach for Residential Energy Management: Current State and Future Directions

In this work, we an envision Home Energy Management System (HEMS) as a Cyber-Physical System (CPS) architecture including three stages: Data Acquisition, Communication Network, and Data Analytics. In this CPS, monitoring, forecasting, comfort, occupation, and other strategies are conceived to feed a control plane representing the decision-making process. We survey the main technologies and techniques implemented in the recent years for each of the stages, reviewing and identifying the cutting-edge challenges that the research community are currently facing. For the Acquisition part, we define a metering device according to the IEC TS 63297:2021 Standard. We analyze the communication infrastructure as part of beyond 2030 communication era (5G and 6G), and discuss the Analytics stage as the cyber part of the CPS-based HEMS. To conclude, we present a case study in which, using real data collected in an experimental environment, we validate proposed architecture of HEMS in monitoring tasks. Results revealed an accuracy of 99.2% in appliance recognition compared with the state-of-the-art proposals.

Crescent Microstrip Antenna for LTE-U and 5G Systems

The field of wireless cellular network technology has seen a significant development in recent years, allowing the emergence of many new applications in addition to the traditional mobile phone calls. We are currently implementing the 5G system, which is replacing the previous cellular technologies on the market. Parallel to the development of cellular technologies, wireless local networks based on the IEEE 802.11× standards are rapidly spreading. The desire to use the advantages of both mobile telephony and wireless local networks has led to the idea of integrating the currently used communication systems in one device and requires a well-designed antenna, which should be given a lot of attention when designing the radio system. This article presents the proposed model of a two-band microstrip antenna for which the main assumption is its operating frequencies in the LTE-U (LTE-Unlicensed) band and one of the 5G system bands. The antenna dimensions and parameters have been calculated, simulated, and optimized using CST Microwave Studio software. The developed antenna has a compact structure with dimensions of (60 × 40 × 1.57) mm. The dielectric material RT Duroid 5880 with a dielectric constant εr = 2.2 and thickness h = 1.57 mm was used as a substrate for the antenna construction. The article presents an analysis of the results of simulation and measurements of selected electrical parameters and radiation characteristics of the proposed antenna. The antenna described in the article, working in 5G systems and LTE-U systems, is characterized by two operating bands with center frequencies equal to 3.52 GHz and 5.37 GHz, a low reflection coefficient (for resonances −31.54 dB and −23.16 dB), a gain value of 4.45 dBi, a wide frequency band of 3.0 GHz (68.18%), and a high energy efficiency in the range of 80–96.68%.

A New Vehicle Dataset in the City of Los Angeles for V2X and Machine Learning Applications

The fifth-generation (5G) network is the current emerging technology that meets the increasing need for higher throughputs and greater system capacities. It is expected that 5G technology will enable many new applications and services. Vehicle-to-everything (V2X) communication is an example of an application that is supported by 5G technology and beyond. A V2X communication system allows a vehicle to be connected to an entity, such as a pedestrian, another vehicle, infrastructure, and a network, to provide a robust transportation solution. It uses many models and strategies that are usually based on machine learning (ML) techniques, which require the use of a vehicle dataset. In this paper, a real vehicle dataset is proposed that was generated in the city of Los Angeles (LA). It is called the Vehicle dataset in the city of LA (VehDS-LA). It has 74,170 samples that are located on 15 LA streets and each sample has 4 features. The LA dataset has been opened to allow researchers in V2X and ML fields to use it for academic purposes. The main uses of the VehDS-LA dataset are studies related to 5G networks, vehicle automation, or ML-Based vehicle mobility applications. The proposed dataset overcomes limitations experienced by previous related works.

Design, Development, and Evaluation of 5G-Enabled Vehicular Services: The 5G-HEART Perspective

The ongoing transition towards 5G technology expedites the emergence of a variety of mobile applications that pertain to different vertical industries. Delivering on the key commitment of 5G, these diverse service streams, along with their distinct requirements, should be facilitated under the same unified network infrastructure. Consequently, in order to unleash the benefits brought by 5G technology, a holistic approach towards the requirement analysis and the design, development, and evaluation of multiple concurrent vertical services should be followed. In this paper, we focus on the Transport vertical industry, and we study four novel vehicular service categories, each one consisting of one or more related specific scenarios, within the framework of the “5G Health, Aquaculture and Transport (5G-HEART)” 5G PPP ICT-19 (Phase 3) project. In contrast to the majority of the literature, we provide a holistic overview of the overall life-cycle management required for the realization of the examined vehicular use cases. This comprises the definition and analysis of the network Key Performance Indicators (KPIs) resulting from high-level user requirements and their interpretation in terms of the underlying network infrastructure tasked with meeting their conflicting or converging needs. Our approach is complemented by the experimental investigation of the real unified 5G pilot’s characteristics that enable the delivery of the considered vehicular services and the initial trialling results that verify the effectiveness and feasibility of the presented theoretical analysis.

The New Era of Business Digitization through the Implementation of 5G Technology in Romania

The main objective of the present research is to identify the advantages and benefits that the use and implementation of 5G technology has on the development and evolution of the Romanian business environment. The study is based on a theoretical documentation regarding existing information in the field and a descriptive analysis of the evolution of the technology in Romania and worldwide. The research method chosen is a survey based on an opinion poll (questionnaire) to find out the availability of economic entities regarding the implementation of 5G technologies, the foreseen expectations and those realized by the business environment regarding the effects of 5G technologies on the economic activities and the benefits that 5G networks offer them. The analysis of the results of the questionnaire, through the correlations and contingency tables determined, allowed the validation of the research hypotheses, and the results show availability and interest for the implementation of 5G technology (over 69% agree with the 5G implementation over a period of up to 5 years), conditioned by the costs, the high degree of cyber security, and the competitive advantages it can generate. Competition, low productivity, and even external pressures are the main decisive factors in the implementation of 5G. Thus, it can be considered useful to extend the research by identifying possible viable solutions or alternatives, customized for the implementation of 5G technologies for economic entities from different sectors, as well as the analysis of the implementation costs and the potential economic benefits.

Enhancing the Reliability of Communication between Vehicle and Everything (V2X) Based on Deep Learning for Providing Efficient Road Traffic Information

Developing efficient communication between vehicles and everything (V2X) is a challenging task, mainly due to the characteristics of vehicular networks, which include rapid topology changes, large-scale sizes, and frequent link disconnections. This article proposes a deep learning model to enhance V2X communication. Various channel conditions such as interference, channel noise, and path loss affect the communication between a vehicle (V) and everything (X). Thus, the proposed model aims to determine the required optimum interference power to enhance connectivity, comply with the quality of service (QoS) constraints, and improve the communication link reliability. The proposed model fulfills the best QoS in terms of four metrics, namely, achievable data rate (Rb), packet delivery ratio (PDR), packet loss rate (PLR), and average end-to-end delay (E2E). The factors to be considered are the distribution and density of vehicles, average length, and minimum safety distance between vehicles. A mathematical formulation of the optimum required interference power is presented to achieve the given objectives as a constrained optimization problem, and accordingly, the proposed deep learning model is trained. The obtained results show the ability of the proposed model to enhance the connectivity between V2X for improving road traffic information efficiency and increasing road traffic safety.

The Energy Mix Dilemma and Environmental Sustainability: Interaction among Greenhouse Gas Emissions, Nuclear Energy, Urban Agglomeration, and Economic Growth

In this paper we examined the interaction between greenhouse gas emissions, nuclear energy, coal energy, urban agglomeration, and economic growth in Pakistan by utilizing time series data during 1972–2019. The stationarity of the variables was tested through unit root tests, while the ARDL (autoregressive distributed lag) method with long and short-run estimations was applied to reveal the linkages between variables. A unidirectional association between all variables was revealed by performing a Granger causality test under the vector error correction model (VECM) that was extracted during the short-run estimate. Furthermore, the stepwise least squares technique was also utilized to check the robustness of the variables. The findings of long-run estimations showed that GHG emissions, coal energy, and urban agglomeration have an adversative association with economic growth in Pakistan, while nuclear energy showed a dynamic association with the economic growth. The outcomes of short-run estimations also show that nuclear energy has a constructive association with economic growth, while the remaining variables exposed an adversative linkage to economic growth in Pakistan. Similarly, the Granger causality test under the vector error correction model (VECM) outcomes exposes that all variables have unidirectional association. Furthermore, the outcomes of the stepwise least squares technique reveals that GHG emissions and coal energy have an adverse association with economic growth, and variables nuclear energy and urban agglomeration have a productive linkage to the economic growth in Pakistan. GHG emissions are no doubt an emerging issue globally; therefore, conservative policies and financial support are needed to tackle this issue. Despite the fact that Pakistan contributes less to greenhouse gas emissions than industrialized countries, the government must implement new policies to address this problem in order to contribute to environmental sustainability while also enhancing economic development.

Improvement of 5G Transportation Services with SDN-Based Security Solutions and beyond 5G

The transportation industries forecast that by 2050 more than 50% of vehicles on the road will be autonomous vehicles, and automotive services will dynamically support all vehicles. All of them will be serviced using the latest technology, which includes the Software Defined Network (SDN) and available new generations (5G+ or 6G) at the time. Although many transportation services and rapid facilities are achievable dynamically, transportation services with automation and intelligent actions are still not mature because the legacy of transport services cannot be corporate with the 5G+. These expected problems can be improved through the following possible and manageable approaches: flexible framework of 5G automotive services from the legacy systems, designing energy-efficient and intelligent infrastructures with SDN, and managing security solutions that evolve with the emerging technology. An efficient model (flexible framework) is proposed to secure smart transportation services with a secure and intelligent connected system and security solutions based on the 5G concept. Although 5G is considered in this framework, the method and steps of design and solution phases will be adaptable to the 5G+ framework. Furthermore, the basic properties of SDN allowed us to design a novel approach for measuring data traffic related to transport services and transport management, such as the priority of the transportation services. With the emergence of 5G+ capabilities, transportation services expect more challenges through future user requirements, including dynamic security solutions, minimum latency, maximum energy efficiency (EE), etc. Future automotive services depend on many sensors and their messages received through secure communication systems with 5G+ capabilities. As a result, this theoretical model will prove that 5G capabilities provide security facilities, better latency, and EE within the transportation system. Moreover, this model can be extendable to improve the 5G+ transportation services.

Edge Computing and IoT Analytics for Agile Optimization in Intelligent Transportation Systems

With the emergence of fog and edge computing, new possibilities arise regarding the data-driven management of citizens’ mobility in smart cities. Internet of Things (IoT) analytics refers to the use of these technologies, data, and analytical models to describe the current status of the city traffic, to predict its evolution over the coming hours, and to make decisions that increase the efficiency of the transportation system. It involves many challenges such as how to deal and manage real and huge amounts of data, and improving security, privacy, scalability, reliability, and quality of services in the cloud and vehicular network. In this paper, we review the state of the art of IoT in intelligent transportation systems (ITS), identify challenges posed by cloud, fog, and edge computing in ITS, and develop a methodology based on agile optimization algorithms for solving a dynamic ride-sharing problem (DRSP) in the context of edge/fog computing. These algorithms allow us to process, in real time, the data gathered from IoT systems in order to optimize automatic decisions in the city transportation system, including: optimizing the vehicle routing, recommending customized transportation modes to the citizens, generating efficient ride-sharing and car-sharing strategies, create optimal charging station for electric vehicles and different services within urban and interurban areas. A numerical example considering a DRSP is provided, in which the potential of employing edge/fog computing, open data, and agile algorithms is illustrated.

A Novel Adaptive Approach for Autonomous Vehicle Based on Optimization Technique for Enhancing the Communication between Autonomous Vehicle-to-Everything through Cooperative Communication

Recent autonomous intelligent transportation systems commonly adopt vehicular communication. Efficient communication between autonomous vehicles-to-everything (AV2X) is mandatory to ensure road safety by decreasing traffic jamming, approaching emergency vehicle warning, and assisting in low visibility traffic. In this paper, a new adaptive AV2X model, based on a novel optimization method to enhance the connectivity of the vehicular networks, is proposed. The presented model optimizes the inter-vehicle position to communicate with the autonomous vehicle (AV) or to relay information to everything. Based on the system quality-of-service (QoS) being achieved, a decision will be taken whether the transmitting AV communicates directly to the destination or through cooperative communication. To achieve the given objectives, the best position of the relay-vehicle issue was mathematically formulated as a constrained optimization problem to enhance the communication between AV2X under different environmental conditions. To illustrate the effectiveness of the proposed model, the following factors are considered: distribution of vehicles, vehicle density, vehicle mobility and speed. Simulation results show how the proposed model outperforms other previous models and enhances system performance in terms of four benchmark aspects: throughput (S), packet loss rate (PLR), packet delivery ratio (PDR) and average delivery latency (DL).

Aerial Tramway Sustainable Monitoring with an Outdoor Low-Cost Efficient Wireless Intelligent Sensor

Infrastructures such as aerial tramways carry unique traffic operations and have specific maintenance requirements that demand constant attention. It is common that old structures lack any type of automatization or monitoring systems, relying only on human judgment. Owners are interested in implementing techniques that assist them in making maintenance decisions, but are reluctant to invest in expensive and complex technology. In this study, researchers discussed with the owners different options and proposed a sustainable and cost-efficient solution to monitor the Sandia Peak Tramway operations with just two strategically located acceleration sensors. To maximize the success options researchers worked with the owners and developed a sensor that satisfied their needs. A Low-cost Efficient Wireless Intelligent Sensor 4—Outdoors (LEWIS 4) was developed, tested and validated during the experiment. Two solar-powered units were installed by the tramway staff and recorded data for three days. When retrieved, researchers analyzed the data recorded and concluded that with only two sensors, the acceleration data collected were sufficient to determine the position and location of the tramway cars. It was also found that the sensor on the tower provides data about the cable–tower interaction and the forces caused by the friction on the system, this being a critical maintenance factor. This work summarizes a methodology for infrastructure owners consisting of guidelines to design a sustainable and affordable monitoring approach that is based on the design, development and installation of low-cost sensors.