Low-cost Solution Research Articles

Internet of Things Long-Range-Wide-Area-Network-Based Wireless Sensors Network for Underground Mine Monitoring: Planning an Efficient, Safe, and Sustainable Labor Environment

Underground mines are considered one of the riskiest facilities for human activities due to numerous accidents and geotechnical failures recorded worldwide over the last century, which have resulted in unsafe labor conditions, poor health outcomes, injuries, and fatalities. One significant cause of these accidents is the inadequate or nonexistent capacity for the real-time monitoring of safety conditions in underground mines. In this context, new emerging technologies linked to the Industry 4.0 paradigm, such as sensors, the Internet of Things (IoT), and LoRaWAN (Long Range Wide Area Network) wireless connectivity, are being implemented for planning the efficient, safe, and sustainable performance of underground mine labor environments. This paper studies the implementation of an ecosystem composed of IoT sensors and LoRa wireless connectivity in a data-acquisition system, which eliminates the need for expensive cabling and manual monitoring in mining operations. Laying cables in an underground mine necessitates cable support and protection against issues, such as machinery operations, vehicle movements, mine operator activities, and groundwater intrusion. As the underground mine expands, additional sensors typically require costly cable installations unless wireless connectivity is employed. The results of this review indicate that an IoT LoRaWAN-based wireless sensor network (WSN) provides real-time data under complex conditions, effectively transmitting data through physical barriers. This network presents an attractive low-cost solution with reliable, simple, scalable, secure, and competitive characteristics compared to cable installations and manually collected readings, which are more sporadic and prone to human error. Reliable data on the behavior of the underground mine enhances productivity by improving key performance indicators (KPIs), minimizing accident risks, and promoting sustainable environmental conditions for mine operators. Finally, the adoption of IoT sensors and LoRaWAN wireless connectivity technologies provides information of the underground mine in real-time, which supports better decisions by the mining industry managers, by ensuring compliance with safety regulations, improving the productive performance, and fostering a roadmap towards more environmentally friendly labor conditions.

Research on the Cultural Factors of Insufficient Expression of Emotion in the Application of AIGC Technology in Film Production

This study discusses the application of AIGC technology in film production and its shortcomings in emotional expression. AIGC technology provides efficient, low-cost solutions in multiple aspects of film production, such as script writing, special effects production and image generation. However, AIGC technology still presents challenges in emotional expression and accurate communication of cultural context. This paper analyzes the application status of AIGC technology in movies and points out its limitations in character expression, tone of character lines, and background construction. It is found that the emotional expression of characters generated by AIGC often lacks delicacy and cannot perfectly present complex emotional changes, especially for the emotional expression in a specific cultural background. To this end, the article suggests that the AIGC technology should play a greater role in film production by enriching the emotional and cultural data of the AIGC model and strengthening the deep understanding of text and images.

Studies of Quantum Dots in Light-Emitting Diodes

Quantum dots are regarded as a revolutionary material especially in display and lighting applications due to their excellent optical properties. Their high quantum efficiency, high color purity, low-cost solution processability, and tunable emission wavelength, facilitate the realization of their potential for display applications. Therefore, researchers have made a lot of effort in the development and characterization of quantum dot light-emitting diodes (QD-LEDs) to achieve high color purity and brightness in light-emitting devices. Meanwhile, with the aim of commercialization, inefficiency, instability, and cost seem to be inevitable challenges that need to be faced. Progression and challenges of using quantum dots in light-emitting diodes are two aspects that are concentrated on in this review. It also affords methods to tackle these challenges. Lastly, the potential applications of QD-LEDs in displays and lighting are investigated. Their potential to revolutionize various industries are also highlighted. By overcoming current limitations and capitalizing on emerging opportunities, QD-LEDs technology will have further applications. This work will help promote in-depth research on QD-LEDs.

Secure low-cost photovoltaic monitoring system based on LoRaWAN network and artificial intelligence

The advanced study will focus on developing a secure and cost-effective photovoltaic monitoring system using Long Range Wide Area Network (LoRaWAN) and Artificial Intelligence technologies for highly risky missions. With the world shifting to using renewable energy, the development of secure and efficient cost-effective monitoring systems for photovoltaic installations becomes very important. However, most of the solutions in use for PV installation monitoring are characterized by high costs, hence their limited use, especially in developing regions. In this regard, the present work presents country-specific protocols designed for the country of Turkey. The proposed system in this study is expected to offer real-time monitoring and data collection at a very meager cost by utilizing inexpensive microcontrollers and sensors. The accuracy rate demonstrated by the research is highly above board: 97.65%. It costs $210, with a very low power consumption of 0.5W and a range of 10 km. The major features underpin real-time monitoring with wide area coverage for effectiveness and efficiency in PVs monitoring. Test results in many places around Turkey have turned out reliable and accurate to justify a possible reduction in operational costs without compromising the quality of data received. This design is reinforced by a detailed mathematical model that assures one of its thorough analysis in performance. There is custom-built firmware that enhances communication efficiency and ensures data integrity in implementation. Comparative studies carried out with existing technologies indicate that the proposed system is cost-effective and operationally sound. This work gives a scalable, low-cost solution that probably might raise the uptake of PV systems in economically constrained areas.

An Improved Velocity-Aided Method for Smartphone Single-Frequency Code Positioning in Real-World Driving Scenarios

The availability of Global Navigation Satellite System (GNSS) raw observations in smartphones has driven research into low-cost GNSS solutions, especially in challenging urban environments, which have garnered significant attention from scholars in recent years. This study proposes an improved smartphone-based velocity-aided positioning method and conducts vehicle-mounted experiments in urban roads representing typical scenarios. The results show that when transitioning from low- to high-multipath environments, the number of visible satellites and carrier phase observations are highly sensitive to environmental factors, with frequent multipath effects. The introduction of robust pre-fit and post-fit residual algorithms has proven to be an effective quality control method. Additionally, using more refined observation models and appropriate parameter estimation algorithms led to a slight 6% improvement in velocity performance. The improved Kalman filter position estimation model (KFSPP-P) strategy, by incorporating velocity uncertainty into the state estimation process, overcomes the limitations of conventional velocity-aided smartphone positioning methods (KFSPP-V) in complex urban environments. In low-multipath environments, the accuracy of the KFSPP-P strategy is comparable to that of KFSPP-V, with an approximate 8% improvement in horizontal accuracy. However, in more challenging environments, such as tree-lined roads and urban environments, the KFSPP-P strategy shows significant improvements, particularly enhancing horizontal positioning accuracy by approximately 50%. These advancements demonstrate the potential of using smartphones to provide reliable positioning services in complex urban environments.

MoiréTag: A Low-Cost Tag for High-Precision Tangible Interactions without Active Components

In this paper, we present MoiréTag—a novel tag-like device that magnifies displacement without active components for indirect sensing of subtle tangible interactions. The device consists of two overlapping layers of stripe patterns with distinct pattern frequencies. These layers create Moiré fringes that can move faster than the actual movement of a layer. Using a customized image processing pipeline, we show that MoiréTag can reliably detect sub-mm movement in real-time (mean error = 0.043 mm) under varying lighting conditions, camera angles, and camera distances. We also demonstrate five applications of MoiréTag to showcase its potential as a low-cost solution to capture and monitor small changes in movement and other physical properties, such as force and volume, by converting them into displacement.

An affordable operational oil spill monitoring system in action: A diachronic multiplatform analysis of recent incidents in the southern Gulf of Mexico

The coexistence of marine sensitive areas with the oil industry requires robust preparedness and rapid response capabilities for monitoring and mitigating oil spill events. Scientifically proven satellite-based methods for the visual detection of oil spills are widely recognized as effective, low-cost, transferable, scalable, and operational solutions, particularly in developing economies. Following meticulous design and implementation, we adopted and executed a relatively low-cost operational monitoring and alert system for oil spill detection over the ocean surface and alert issuance. We analyzed over 1500 satellite images, issuing over 70 warning reports on oil slicks and spills in the southern Gulf of Mexico. To assess the system’s efficiency and performance, we leveraged data from three major oil spill incidents in the study region during June and July of 2023 in the study region, covering a maximum area of 669 km2 and tracked for 12 to 24 days. We documented the evolution of these oil spills by integrating satellite sensing data with on-site Lagrangian drifting buoys, a network of high-frequency radars, and citizen reports to validate the outcomes of this system. We generated timely technical information on the spill’s evolution, informing decision-makers and local community leaders to strengthen their mitigation response capabilities. Additionally, we developed a robust database with spectral and spatiotemporal features of satellite-detected oil, thereby contributing to advancing the scientific understanding of sea surface dynamics related to natural and anthropogenic oil sources. This study also highlights immediate-, medium-, and long-term research agendas and establishes a reference for a sustained, transferable, and operational oil spill monitoring system.

Storing Excess Solar Power in Hot Water on Household Level as Power-to-Heat System

PV technology has become widespread in the Netherlands, reaching a cumulative installed capacity of 22.4 GWp in 2023 and ranking second in the world for solar PV per capita at 1268 W/capita. Despite this growth, there is an inherent discrepancy between energy supply and demand during the day. While the netting system in the Netherlands can currently negate the economic drawbacks of this discrepancy, grid congestion and imbalanced electricity prices show that improvements are highly desirable for the sustainability of electricity grids. This research analyzes the effectiveness of a Power-to-Domestic-Hot-Water (P2DHW) system at improving the utilization of excess PV electricity in Dutch households and compares it to similar technologies. The results show that the example P2DHW system, the WaterAccu, compares favorably as a low cost and flexible solution. In particular, for twelve different households differing in size (1–6 occupants), PV capacity (2.4–8 kWp), and size of hot water storage boiler (50–300 L), it is shown that the total economic benefits for the period 2024–2032 vary from −€13 to €3055, assuming the current net metering scheme is abolished in 2027. Only for large households with low PV capacity are the benefits a little negative. Based on a multi-criteria analysis, it is found that the WaterAccu is the cheapest option compared to other storage options, such as a home battery, a heat pump boiler, and a solar boiler. A sensitivity study demonstrated that these results are overall robust. Furthermore, the WaterAccu has a positive societal impact owing to its peak shaving potential. Further research should focus on the potential of the technology to decrease grid congestion when implemented on a neighborhood scale.

Evaluating antenna phase center variation effects on tropospheric delay retrieval using a low-cost dual-frequency GNSS receiver

Abstract This study examines the impact of Phase Center Variation (PCV) corrections on Zenith Wet Delay (ZWD) accuracy using a low-cost U-blox ZED-F9P receiver paired with three different antenna configurations: the high-grade TRM57971 antenna, the moderate-grade AS-ANT3BCAL antenna, and the low-cost ANN-MB-00 antenna. Among the three antennas evaluated, the low-cost antenna exhibited the largest PCV magnitude and a pronounced elevation angle dependence. In contrast, the other two antennas demonstrated lower levels of PCV variation. Without PCV corrections, the low-cost antenna showed significant ZWD biases compared to reference values. Applying PCV corrections significantly improved its accuracy, reducing bias and RMS by 88% and 79%, respectively. Moderate- and high-grade antennas experienced minimal improvement with correction. All antennas exhibited remarkable day-to-day repeatability in their residual patterns, despite variations observed in the RMS of phase residuals. This observed repeatability is likely attributable to the presence of unmodeled multipath contributions. The variations in RMS, in turn, can be primarily ascribed to inherent differences in multipath resistance among the antenna designs. This study highlights the critical role of PCV corrections for accurate ZWD estimation with low-cost GNSS receivers. Future research should prioritize the acquisition of manufacturer-provided calibration data for low-cost antennas to streamline and enhance the accuracy of PCV correction applications. Moreover, efforts should be directed toward developing innovative solutions, such as low-cost, multipath-resistant antennas or advanced signal processing algorithms, to mitigate the impact of multipath errors. By addressing these areas, low-cost GNSS solutions can become more reliable and cost-effective tools for tropospheric delay estimation.

Roles of shallow energy level defect states on amplified spontaneous emission enhancement of CH3NH3PbBr3 perovskite crystals

Abstract In this work, we demonstrated the role of shallow energy level defect states on the emission of CH3NH3PbBr3 perovskite polycrystals under laser excitation. The perovskite polycrystals were synthesized by a simple, one-step, low-cost solution self-assembled method. By adjusting the sample preparation temperature from 303 to 373 K, we could manipulate the number of shallow energy level defect states, which were evaluated through low-temperature photoluminescence measurement. This led to an evolution of the CH3NH3PbBr3 perovskite polycrystals’ emission from amplified spontaneous emission to random lasing emission. As a result, the most efficient lasing threshold of 4 μJ mm−2 was achieved with the CH3NH3PbBr3 perovskite polycrystals synthesized at the optimum temperature of 333 K. Furthermore, the surface morphologies and the crystal structure of the CH3NH3PbBr3 perovskite polycrystals were also taken into consideration to unravel the role of defects in the CH3NH3PbBr3 perovskite polycrystals.

Cu–Cu joint with great strength using In/Sn–58Bi hybrid soldering at low temperature (90 °C)

This study investigates Cu single-sided solder joints using hybrid soldering (In + Sn58Bi) at reflow temperatures ranging from 80 to 130 °C. The wetting angles of 27° at 90 °C and 22° at 130 °C demonstrated good wettability. The hybrid solders were composed of γ-In(Sn, Bi) and Bi(In, Sn)2 phases, forming Cu6(In, Sn)5 interfacial intermetallic compounds (IMCs). Thermodynamic calculations proved that the hybrid soldering possessed a low liquid temperature of 86.8 ° C, making it suitable for low-temperature applications. The hybrid solders demonstrated notable mechanical performance, with microhardness values exceeding 10 HV—higher than Sn–52In solder (6 HV). Sandwich hybrid-solder joints, reflowed at 90 and 130 ° C, outperformed Sn–52In soldering strength (30.1 and 35.5 MPa) by over 135% and 175%. Additionally, the hybrid solder contains only 41.9 wt% In, lower than Sn–52In, reducing material costs. This study reveals the hybrid solder system offers a promising low-cost and good-strength solution for low-temperature soldering applications.

Dedicated low-cost electronic ocarina for people with COPD: Rationale and prototype development

ABSTRACT Introduction Chronic obstructive pulmonary disease (COPD) is a condition characterized by airflow obstruction which can lead to physical and psychosocial challenges, with a higher prevalence in developing countries. Non-pharmacological interventions for this group of people include pulmonary rehabilitation as well as music interventions. Although music technology was recommended to adjust to the user’s breathing capacity for music-making and to gather information about their performance, music therapy trials used acoustic wind instruments for their rehabilitation. This interdisciplinary project aims to develop a dedicated electronic wind instrument for people with COPD. Method This project follows a systematic prototype methodology that includes product research, instrument development, and user validation. Based in Brazil, our team has decided on an electronic ocarina based on its cultural features, its popularity as a digital application, and its potential for respiratory training. Unlike existing technologies, the prototype intends to be dedicated and a low-cost solution. Results The development process includes decision making about the appropriate mouthpiece, sensors, Arduino, pushbuttons, 3-D printing projects, building a MIDI interface and a dedicated software. This is an ongoing project, and our team is in the MIDI interface development stage. We aim to run the first hardware trial with users so that we can integrate their feedback into the functional prototype and the dedicated software for the following trials. Discussion This project’s strengths rely on the innovation of building viable electronic wind instruments that can facilitate self-management of people with COPD in developing countries, where access to healthcare can be challenging.

Designing Contact Independent High-Performance Low-Cost Flexible Electronics.

Organic semiconductors enable low-cost solution processing of optoelectronic devices on flexible substrates. Their use in contemporary applications, however, is sparse due to persistent challenges in achieving the requisite performance levels in a reliable and reproducible manner. A critical bottleneck is the inefficiency associated with charge injection. Here, large-scale simulations are employed to identify operational windows where key device parameters that are difficult to control experimentally, such as the contact resistance, become less consequential to overall device functionality. This design methodology overcomes injection barrier limitations in organic field-effect transistors (OFETs), leading to high charge carrier mobility and significantly expanding the range of suitable electrode materials. Leveraging this new understanding, all-organic, solution-deposited OFETs are successfully fabricated on flexible substrates. These devices incorporate printed contacts and showcase mobilities exceeding 5cm2Vs-1. These results provide a route for accessing the fundamental limits of material properties even in the absence of ideal contacts - a critical step in establishing reliable structure/property relationships and optimal material design paradigms. While reducing the injection barrier and contact resistance remains critical for achieving high OFET performance, this work demonstrates a path toward consistently achieving high charge carrier mobility through device geometry design, ultimately reducing processing complexity and cost.

Optimizing Routing Protocol Design for Long-Range Distributed Multi-Hop Networks

The advancement of communication technologies has facilitated the deployment of numerous sensors, terminal human–machine interfaces, and smart devices in various complex environments for data collection and analysis, providing automated and intelligent services. The increasing urgency of monitoring demands in complex environments necessitates low-cost and efficient network deployment solutions to support various monitoring tasks. Distributed networks offer high stability, reliability, and economic feasibility. Among various Low-Power Wide-Area Network (LPWAN) technologies, Long Range (LoRa) has emerged as the preferred choice due to its openness and flexibility. However, traditional LoRa networks face challenges such as limited coverage range and poor scalability, emphasizing the need for research into distributed routing strategies tailored for LoRa networks. This paper proposes the Optimizing Link-State Routing Based on Load Balancing (LB-OLSR) protocol as an ideal approach for constructing LoRa distributed multi-hop networks. The protocol considers the selection of Multipoint Relay (MPR) nodes to reduce unnecessary network overhead. In addition, route planning integrates factors such as business communication latency, link reliability, node occupancy rate, and node load rate to construct an optimization model and optimize the route establishment decision criteria through a load-balancing approach. The simulation results demonstrate that the improved routing protocol exhibits superior performance in node load balancing, average node load duration, and average business latency.

Deep Learning-Based Dust Detection on Solar Panels: A Low-Cost Sustainable Solution for Increased Solar Power Generation

The world is shifting towards renewable energy sources due to the harmful effects of fossils fuel-based power generation in the form of global warming and climate change. When it comes to renewable energy sources, solar-based power generation remains on top of the list as a clean and carbon cutting alternative to the fossil fuels. Naturally, the sites chosen for installing solar parks to generate electricity are the ones that get maximum solar radiance throughout the year. Consequently, such sites offer challenges for the solar panels such as increased temperature, humidity and high dust levels that negatively affect their power generation capability. In this work, we are more concerned with the detection of dust from the images of the solar panels so that the cleaning process can be done in time to avoid power loses due to dust accumulation on the surface of solar panels. To this end, we utilize state-of-art deep learning-based image classification models and evaluate them on a publicly available dataset to identify the one that gives maximum classification accuracy for dusty solar panel detection. We utilize pre-trained models of 20 deep learning models to encode the images that are then used to train and validate four variants of a support vector machine. Among the 20 models, we get the maximum classification of 86.79% when the images are encoded with the pre-trained model of DenseNet169 and then use these encodings with a linear SVM for image classification.

Justice-centered best practices for accessibility to public buildings in a tier II city: Insights from a Delphi expert consensus

Background Despite beneficial progress in policies, awareness and advocacy, accessibility gaps exist in public buildings in India. Challenges achieving full inclusivity still exist, due to a lack of clear guidance for implementing accessible solutions. Retrofitting older buildings, particularly in developing tier II cities is a major challenge. The authors of this paper aimed to address this issue using a four-round Delphi method to generate a Justice-Centered Best Practices (JCBPs) for accessibility provisions for individuals with mobility disabilities. Methods Conducted in Udupi, the study involved experts including administrators, policy implementers, auditors, advocates, healthcare professionals, individuals with disabilities and their caregivers. In the first round, a 117-item list was generated through triangulation of three methods. In subsequent rounds, experts rated each item using a 5-point Likert scale on feasibility, affordability and priority. Responses were considered valid if the agreement reached ≥80% on the total score. The prioritised list of JCBPs was finalised at a consensus meeting. Results Out of forty-eight experts who began the study, 16 participated in the final meeting. The Wilcoxon signed rank test (p value>0.05) of expert ranking indicated that the scoring of items remained consistent between the two rounds. A machine learning decision tree analysis identified items securing ≥ 80% agreement as the most reliable decision with an accuracy=71.43%. The McNemar’s Test p value=0.79 confirmed consistency of expert scoring on the items with high agreement rates. Conclusion Finally, 33 built and non-built environment items scored highest rank. Stakeholder engagement, use of low-cost technology solutions, coordination between public administrations, funding, good governance practice, awareness, and advocacy were few of the solutions that can help ensure accessibility is in place for individuals with mobility disabilities. The study methodology and findings create a robust foundation for evidence-based JCBPs for accessibility provisions for individuals with mobility disabilities.

A Machine Learning Approach for Predicting Pedaling Force Profile in Cycling

Accurate measurement of pedaling kinetics and kinematics is vital for optimizing rehabilitation, exercise training, and understanding musculoskeletal biomechanics. Pedal reaction force, the main external force in cycling, is essential for musculoskeletal modeling and closely correlates with lower-limb muscle activity and joint reaction forces. However, sensor instrumentation like 3-axis pedal force sensors is costly and requires extensive postprocessing. Recent advancements in machine learning (ML), particularly neural network (NN) models, provide promising solutions for kinetic analyses. In this study, an NN model was developed to predict radial and mediolateral forces, providing a low-cost solution to study pedaling biomechanics with stationary cycling ergometers. Fifteen healthy individuals performed a 2 min pedaling task at two different self-selected (58 ± 5 RPM) and higher (72 ± 7 RPM) cadences. Pedal forces were recorded using a 3-axis force system. The dataset included pedal force, crank angle, cadence, power, and participants’ weight and height. The NN model achieved an inter-subject normalized root mean square error (nRMSE) of 0.15 ± 0.02 and 0.26 ± 0.05 for radial and mediolateral forces at high cadence, respectively, and 0.20 ± 0.04 and 0.22 ± 0.04 at self-selected cadence. The NN model’s low computational time suits real-time pedal force predictions, matching the accuracy of previous ML algorithms for estimating ground reaction forces in gait.

Development of low-cost MEMS microphone array for sound localization in urban environments

Understanding noise pollution and mitigating its impact on the quality of life in urban environment is a major challenge from a societal and health point of view. In order to monitor and ultimately understand these noisy environments a process of long term acoustic measurements and analysis is required. These urban environments are noisy and obtaining a clear recording of a desired acoustic signal is difficult hence an effective approach is the use of beamforming theory coupled with a microphone array. In this paper a novel approach utilizing compact low-cost microphone arrays equipped with MEMS sensors for continuous sound localization in urban areas is proposed. This approach focuses on leveraging the affordability and scalability of MEMS sensors to deploy distributed acoustic sensor networks across diverse urban locations. The aim is to capture real-time acoustic data, enabling comprehensive monitoring of sound sources and their spatial distribution within the urban environment. This sensor unit can be upgraded with a camera, i.e. acoustic camera, which will provide information on the conditions of the environment where the measurements are performed. This low-cost solution facilitates long-term monitoring, providing valuable insights into the dynamic nature of urban soundscapes.

Development of an application for training management of the maintenance team in a metallurgical industry in the suape industrial complex – cabo de Santo Agostinho

This work presents the development of an application designed to complement traditional training management methods within an organization. The application, developed on the PowerApps platform using a Low-Code approach, aims to facilitate the monitoring and management of employee training in the maintenance department of a company located in the Suape industrial complex, Cabo de Santo Agostinho. Its main objective is to provide a digital platform that allows for the verification of the training status of maintenance technicians, identifying which are in "Attention," "Expired," and/or "OK" status. Traditionally, this data is managed manually, in a time-consuming and error-prone process. The transition to a digital system ensures data accuracy, reduces the time required to access and update information, and improves the overall efficiency of the department's activity scheduling process. During the testing phase, conducted between January and August 2024, comparative data was collected on the training consultation process, before and after the implementation of the application. Preliminary results indicated a significant improvement in the efficiency and productivity of the maintenance department, comparable to other works that used PowerApps as a quick and low-cost solution.

Processing techniques for metrological improvement of low-cost smart meter hardware solution for IEC 61000-4-7 Class I harmonics measurements

The work investigates the feasibility of harmonic analysis implementation on smart meter microcontroller devices, according to IEC 61000-4-30 Class A and IEC 61000-4-7 Class I requirements. The final aim was to evaluate to what extent Class I harmonic analysis can be integrated into existing low-cost hardware platforms for smart metering, which normally have limited hardware features, especially concerning the ADC and the possibility of varying the sampling frequency with high resolution, according to the power system signal frequency. An extended experimental characterization is carried out on a case study device, aimed at analyzing its performances in terms of both measurement accuracy and computational burden. To increase metrological ADC behavior and decrease computational costs, sampling strategies and optimized interpolation algorithm have been implemented and tested verifying the feasibility of harmonic analysis implementation on smart meter microcontroller devices, according to IEC 61000-4-30 Class A and IEC 61000-4-7 Class I requirements.