Remote Technology Research Articles

A decision-analytic method to evaluate the cost-effectiveness of remote monitoring technology for chronic depression.

Advances in mobile apps, remote sensing, and big data have enabled remote monitoring of mental health conditions, but the cost-effectiveness is unknown. This study proposed a systematic framework integrating computational tools and decision-analytic modeling to assess cost-effectiveness and guide emerging monitoring technologies development. Using a novel decision-analytic Markov-cohort model, we simulated chronic depression patients' disease progression over 2 years, allowing treatment modifications at follow-up visits. The cost-effectiveness, from a payer's viewpoint, of five monitoring strategies was evaluated for patients in low-, medium-, and high-risk groups: (i) remote monitoring technology scheduling follow-up visits upon detecting treatment change necessity; (ii) rule-based follow-up strategy assigning the next follow-up based on the patient's current health state; and (iii-v) fixed frequency follow-up at two-month, four-month, and six-month intervals. Health outcomes (effects) were measured in quality-adjusted life-years (QALYs). Base case results showed that remote monitoring technology is cost-effective in the three risk groups under a willingness-to-pay (WTP) threshold of U.S. GDP per capita in year 2023. Full scenario analyses showed that, compared to rule-based follow-up, remote technology is 74 percent, 67 percent, and 74 percent cost-effective in the high-risk, medium-risk, and low-risk groups, respectively, and it is cost-effective especially if the treatment is effective and if remote monitoring is highly sensitive and specific. Remote monitoring for chronic depression proves cost-effective and potentially cost-saving in the majority of simulated scenarios. This framework can assess emerging remote monitoring technologies and identify requirements for the technologies to be cost-effective in psychiatric and chronic care delivery.

Exploring Educators' Perceptions and Experiences of Online Teaching to Foster Caring Profession Students' Development of Virtual Caring Skills: Sequential Explanatory Mixed Methods Study.

Professionals in caring disciplines have been pivotal in advancing virtual care, which leverages remote technologies to deliver effective support and services from a distance. Educators in these caring professions are required to teach students the skills and competencies needed to provide high-quality and effective care. As virtual care becomes more integral, educators must equip students in these fields with both interpersonal and technological skills, bridging traditional hands-on learning with digital literacy. However, there is a gap in evidence exploring educators' perceptions and experiences of teaching caring profession students about virtual caring skills within online environments. This study aims to better understand caring profession educators' online teaching experiences to foster student development of virtual caring skills and competencies. We used a sequential explanatory mixed methods approach that integrated a cross-sectional survey and individual interviews with educators from caring professions to better understand caring professional educators' online teaching experiences to foster student development of virtual caring skills and competencies. The survey's primary objectives were to examine the various elements of existing e-learning opportunities, delve into educators' perspectives and encounters with these opportunities, and identify the factors that either facilitated or hindered online teaching practices to support students in developing virtual caring skills and competencies. The individual interview guides were based on survey findings and a systematic review of the evidence to gain deeper insights into educators' experiences and perspectives. A total of 82 survey participants and 8 interview participants were drawn from educators in the fields of education, medicine, nursing, and social work. Various instructional methods were used to help students develop virtual caring skills, including reflections on learning, online modules, online discussion boards, demonstrations of remote care, and consultation with clients. There was a statistically significant difference between educators' level of experience teaching online and their satisfaction with online teaching and learning technologies (P<.001) and between educators' faculties (departments) and their satisfaction with online teaching and learning technologies (P=.001). Participants identified barriers (time constraints, underdeveloped curriculum, decreased student engagement, and limited access to virtual caring equipment and technology), facilitators (clearly defined learning objectives, technology software and support, teaching support, stakeholder engagement, and flexibility), and principles of teaching virtual caring skills in online environments (connection, interaction, compassion, empathy, care, and vulnerability). Our study identifies the barriers, facilitators, and principles in teaching virtual caring skills, offering practical strategies for educators in caring professions. This study contributes to the growing body of educational research on virtual caring skills by offering educator insights and suggestions for improved teaching and learning strategies in caring professions' programs. As educational practices evolve, future research should explore how traditionally in-person educators can effectively teach virtual caring skills across diverse contexts.

Research on force feedback technology for industrial robot

Force feedback technology plays a crucial role in the field of robot control, especially in scenarios involving precise task execution. With the increasing application of robots in industrial production and automation, traditional control methods based on preset paths can no longer meet the requirements of complex and changing working environments. The force feedback system senses the force information of the robot during operation, adjusts the robot's actions and force in real time, ensures that appropriate force can be maintained during operation, and prevents damage to the working object or reduced task accuracy. While this technology primarily enhances robotic flexibility in complex operations, it has also become instrumental in advancing human-robot collaboration. By combining human perception and regulation abilities, robots are able to perform more challenging tasks. In recent years, force feedback systems that combine multi-sensor fusion, visual control, and remote operation technologies have gradually become one of the core solutions for solving force control problems in robot task execution, providing strong guarantees for safety, accuracy, and efficiency in automated production.

Chimpanzee Activity and Behavioral Diversity Extends Across 24 Hours in Both Captive and Wild Settings.

Studying nocturnal behavior is crucial for understanding the full scope of a species' behavioral flexibility so as to inform the conservation of wild populations and the care of captive individuals. However, this aspect of primate behavior is understudied, especially in great apes, which exhibit some of the widest documented behavioral diversity and flexibility. Our investigation is among the first to systematically compare the 24 h activity patterns and behavioral activities of captive chimpanzees (Saint Louis Zoo, USA) with those of wild chimpanzees (three sites across the Nouabalé-Ndoki National Park in the Republic of Congo) and a published data set of the nocturnal behavior of all chimpanzee subspecies. Furthermore, we examined the influence of human activity and changes to the group's composition on the activity patterns and nocturnal behaviors of the zoo-living chimpanzees. Our results reveal that the zoo-living chimpanzees exhibit significantly different activity patterns compared to their wild counterparts, with increased nocturnal activity (particularly in the early morning) and more observations of feeding and social behaviors at night. Additionally, the absence of human visitors and a change in the group's composition were found to influence these activity patterns. These findings underscore the importance of integrating more holistic approaches to captive primate care and wild primate conservation. This study also highlights the immense potential of implementing remote monitoring technology, such as video camera traps, across contexts. Such data that extend across contexts benefit not only the captive and wild great apes but also provide opportunities for caregivers, conservation managers, and students who are involved in these collaborative initiatives.

Remote terminal-oriented power line carrier communication technology

Remote terminal-oriented power line carrier communication technology

Weather and Marine Aquaculture Workers’ Safety in Atlantic Canada

ABSTRACT Objective Marine aquaculture workers are at high risk of injury and fatalities. Understanding the role of weather in occupational safety and health (OSH) in marine aquaculture is important for work design, planning, and for safety management and hazard reduction, but there is limited research on this subject. Methods Using findings from a review of research and grey literature and from key informant interviews and roundtable discussions in Atlantic Canada, this paper explores the impact of weather-driven hazards on marine aquaculture in Northern and temperate regions, along with the strategies employed to mitigate these impacts. Results Findings indicate primary concerns for aquaculture OSH include sun and cold exposures; working on and under surface ice; strong winds; waves; current; reduced visibility; and ice build-up. Conclusions Key changes that could help reduce weather-related injury risk include improved forecasting capacity; improved reporting of weather conditions at the time of an incident in administrative injury and fatality data; incorporation of weather-related OSH hazards and risks in industry risk assessments; mechanization, including increased use of remote operation technologies on farm sites; and improved infrastructure standards and design.

Financial Health Management of Otolaryngology by Telemedicine: Opportunities and challenges

The COVID-19 pandemic has impacted the world and medical branches are affected too, this article shows otolaryngology (Otlogy) management like patient care in the outpatient (OP) remotely by the implementation of business strategy of telemedicine (TME). The research explains how the applications of management strategies in TME for Otlogy can reduce the medical expenses and also offer profits to the medical practitioners. This article suggests the advantages of TME for (Otlogy) related health risks and advises health centers to implement the business strategy of TME which can provide services using remote Information Communications Technology (ICT) to evade exposure risks to HCR providers, patients, and the general community. The realization of TME, or virtual services, can help the Otolaryngologists to provide needed care to patients amid COVID pandemic. This research illustrates the challenges in the application of TME and benefits to the patients as well as for the medical professionals.

Smart Automation for Enhanced Lighting through Remote Control Systems in Coal Mining Areas

The coal mining industry faces significant safety challenges due to hazardous working environments and manual monitoring processes, particularly involving Tower Lamp units. These activities expose employees to risks, including harsh weather and operational incidents, leading to potential accidents and financial losses. This study proposes an intelligent safety control system employing real-time remote monitoring technology to mitigate these risks. The system enables centralized control of Tower Lamps, reducing manual interactions, improving energy efficiency through automated lighting adjustments, and enhancing workplace safety. The methodology includes designing and implementing a monitoring system with remote control capabilities supported by real-time data analysis. Expected outcomes include reduced work accidents, optimized lighting management, and streamlined operations, showcasing a scalable model for broader industrial applications. This technological innovation demonstrates a practical solution for improving safety and operational efficiency in coal mining environments.

Tantangan dalam Pendidikan MIPA dan Solusinya untuk Pendidikan Inklusif

MIPA education (Mathematics and Natural Sciences) plays a strategic role in developing excellent human resources in the modern era. However, the disparity in access to and the quality of MIPA education in Indonesia remains a significant challenge, particularly in remote areas. This article aims to identify the factors contributing to the gap in MIPA education, analyze its impact on learning quality, and propose solutions to address the issue. The main causes of this disparity include inadequate infrastructure, uneven distribution of teachers, and technological and socio-economic barriers. The consequences range from low student interest in science and technology to inequality in educational quality across regions. This article recommends strengthening policies for equitable education, enhancing remote learning technologies, and fostering cross-sector collaboration to create inclusive and sustainable MIPA education.

Political participation and digital communications of Russians after the start of the SMO: features and main forms

The article is devoted to identifying key changes in the practices of political participation of Russian citizens during the period of a Special military operation on the territory of Ukraine, caused, among other things, by the transformation of public political discourse and the digital environment. Analyzing the phenomenon of social consolidation in the conditions of ITS, key models of political participation and changes in media consumption of Russians over the past two years, the author concludes that after February 24, 2022, a certain transformation of public discourse and structure of media consumption, as well as related practices of political participation of Russians, took place in Russia. There is a differentiation of the socially active part of the population into two unequal groups: on the one hand, a dissenting protest minority, whose main form of political participation and "statements" were emigration or spontaneous protests; on the other hand, a consolidated patriotic majority expressing support for the activities of the country's leadership through traditional as well as new forms of participation: charity, volunteering, "pro-government" electoral behavior, information and campaigning work. It is also noted that the prevailing practices of political participation due to the use of digital technologies today are volunteer activities (including "virtual volunteering"), protest political participation, as well as conventional practices of electoral participation using remote electronic voting technologies.

Patients' and Clinicians' Experiences Using a Real-Time Remote Monitoring System for Chemotherapy Symptom Management (ASyMS): Qualitative Study.

Patients receiving chemotherapy require ongoing symptom monitoring and management to optimize their outcomes. In recent years, digital remote monitoring interventions have emerged to provide enhanced cancer care delivery experiences to patients and clinicians. However, patient and clinician experiential evaluations of these technologies are rare. Therefore, we explored user experiences and perceptions of one such intervention-Advanced Symptom Management System (ASyMS)-after its scaled deployment in the context of the Electronic Symptom Management System Remote Technology (eSMART) trial. The eSMART trial was a large, multicenter randomized controlled trial to evaluate the efficacy of ASyMS in 12 clinical sites in 5 European countries. In this qualitative study, both patients' and clinicians' experiences of using ASyMS for up to 6 cycles of chemotherapy were explored to understand the impact of ASyMS on patients' experiences, clinical practice, and supportive care delivery. For this analysis, individual, semistructured, one-to-one interviews with 29 patients with breast, colorectal, and hematological cancers and 18 clinicians from Austria, Greece, Ireland, Norway, and the United Kingdom were conducted. Interviews focused on patients' and clinicians' experiences of using ASyMS, care organization and changes in practice following the introduction of ASyMS, perceived changes in care associated with the use of ASyMS, and its potential for future integration into routine chemotherapy care pathways. Thematic analysis identified several themes that describe patients' and clinicians' experiences using ASyMS. One central orienting theme-ASyMS as a facilitator of change-was supported by 5 key themes associated with human and technology monitoring: reassurance, enhanced communications and relationships, knowing what is "normal" and what is to be expected, enhancing cancer care experiences, and informing future cancer care. This study is the first to evaluate both patients' and clinicians' experiences of using a digital health intervention to remotely monitor chemotherapy symptoms across 5 countries. Experiences with ASyMS were positive from both patients' and clinicians' perspectives, although some improvements to support the wider-scale rollout and sustained implementation were identified. Overall, this study demonstrates that real-time remote monitoring systems can help patients feel more reassured during their chemotherapy treatments and can help clinicians provide the right care, at the right time, and in the right place. ClinicalTrials.gov NCT02356081; https://clinicaltrials.gov/study/NCT02356081. RR2-10.1136/bmjopen-2016-015016.

Predicting main behaviors of beef bulls from accelerometer data: A machine learning framework

Traditional methods to monitor free-range cattle, such as breeding beef bulls, are time-consuming. However, most current remote monitoring technologies operate at high sampling rates, making their use on bulls impractical due to their high battery consumption. Therefore, this study aims to describe and evaluate a machine-learning framework to predict the behaviors of beef bulls from raw accelerometer data at low sampling rates. Collars with 3D-accelerometers were deployed on 33 bulls, recording accelerometer data at 0.5 Hz (22 bulls in 2020 and 2021) or 1.0 Hz (11 bulls in 2023). Videos of bulls in pens, synched with the accelerometer by time, were recorded and analyzed. The behaviors investigated were grazing (GR), resting (RE), ruminating (RU), walking (WA), and in 2023, fighting (FI). Primary labels of activity (AC), corresponding to GR, WA, and FI, and non-activity (NA), corresponding to RE and RU, were assigned. Two datasets were created from data sampled at 1.0 Hz and 0.5 Hz. Then, behavioral events with duration within the inferior 0.05 quantile of the distribution for each behavior were removed, integrated measures of motion were calculated, and segmentation into consecutive 20s time-windows was performed. Afterward, 132 frequency and time-domain features were extracted, and bulls’ ages were added as a physical feature. Two bulls from each year and dataset were segregated to form independent test sets. A leave-one-animal-out cross-validation (LOAO) was applied to Extratree classifiers to select relevant features. The final classifier was built in a hierarchical structure using XGBoost classifiers to make predictions on two levels: (1) distinguishing between AC and NA, and (2) categorizing AC into GR, WA, FI, and NA into RE or RU. This model was evaluated using LOAO and test sets for each dataset, and precision and sensitivity were calculated for each behavior. Matthews Correlation (MCC) and Cohen's Kappa (CK) coefficients were calculated for the overall assessment of the models’ levels. Comparisons of metrics obtained on LOAO and test sets were performed using the Wilcoxon Sum Rank and the Wilcoxon Signed Rank test. The LOAO MCC for 1.0 Hz (1st level=0.98±0.01, 2nd level=0.92±0.02) was higher than 0.5 Hz (1st level=0.83±0.20, 2nd level=0.71±0.20). In 1.0 Hz, all behaviors presented mean precision and sensitivity above 0.7, except the sensitivity of FI (LOAO = 0.47±0.06, test set = 0.63±0.18). In 0.5 Hz, the exception was the sensitivity of WA (LOAO = 0.58±0.28, test set = 0.68±0.06) and the sensitivity of RU in the test set (0.54 ± 0.26). Therefore, the proposed framework can be used to predict the behaviors of beef bulls from accelerometers sampling at 0.5 Hz or 1.0 Hz, although better results are observed at 1.0 Hz. Caution should be exercised for predicting FI at 1.0 Hz and WA at 0.5 Hz.

Heart Failure Beyond the Diagnosis: A Narrative Review of Patients' Perspectives on Daily Life and Challenges.

Heart failure (HF) is a complex syndrome that significantly affects patients' physical, psychological, and socioeconomic well-being. Despite advances in guideline-directed medical therapy (GDMT), such as ACE inhibitors, beta-blockers, and SGLT2 inhibitors, HF continues to have a high global burden, with over 64 million affected worldwide and a five-year mortality rate of 50%. HF disrupts various life aspects, especially for younger patients (aged 35-55), who often face career interruptions due to severe symptoms like fatigue and frequent hospitalizations. These patients may struggle to maintain employment, resulting in financial instability compounded by high healthcare costs. Moreover, reduced exercise capacity and sexual dysfunction negatively impact patients' quality of life. The psychological toll of HF is profound, with many patients experiencing depression, anxiety, and stress. However, a positive mindset has been shown to improve survival rates, underscoring the need for holistic management approaches. Interventions like cognitive behavioral therapy (CBT) and remote monitoring technologies such as CardioMEMS offer promising avenues to improve quality of life and reduce hospitalizations. This review highlights the importance of a multidisciplinary, patient-centered approach to HF management. Tailoring care to align with individual goals, integrating psychosocial support, and enhancing patient education are vital in addressing both the clinical and personal challenges of HF. By adopting a comprehensive approach, healthcare providers can significantly improve long-term outcomes and quality of life for HF patients.

Exploring Health Informatics for Chronic Disease Management: A Systematic Review of Tools and Outcomes

Chronic diseases represent a significant burden on healthcare systems worldwide, necessitating innovative approaches to enhance patient management and improve health outcomes. Health informatics tools, including electronic health records (EHRs), mobile health applications, telemedicine, and predictive analytics, offer promising solutions for managing chronic conditions by facilitating patient engagement, supporting clinical decision-making, and improving healthcare efficiency. This systematic review evaluates recent literature on health informatics tools used in chronic disease management, examining their impact on patient health outcomes, adherence, and healthcare delivery efficiency. Findings reveal that digital health solutions, particularly mobile health applications and remote monitoring technologies, demonstrate substantial benefits in improving patient engagement and adherence to treatment protocols, leading to better disease management and reduced hospitalization rates. However, challenges such as data privacy, interoperability, and limited digital literacy remain significant barriers to widespread implementation. This review highlights the need for continued research to optimize health informatics applications, address implementation challenges, and further integrate these tools into healthcare systems for improved chronic disease management.

Impact of remote social interaction during the COVID-19 pandemic on the cognitive and psychological status of older adults with and without cognitive impairment: A randomized controlled study.

Social isolation and loneliness have both been associated with psychological health and cognitive decline in older adults. This study investigated the impact of social interaction through remote communication technologies during the COVID-19 pandemic on the cognitive and psychological status of older adults with and without cognitive impairment. Participants were recruited from Boston (USA) and Chieti (Italy). The study used a randomized single-blinded controlled crossover design with an intervention (remote social conversations with research staff over 20-minute video or telephone calls three times per week) and a passive control condition, each one of 4-weeks duration. The primary outcome was a composite cognitive score change from baseline to week 4. Secondary outcomes included scales for mood, anxiety, and loneliness. Out of 196 participants recruited from April 2020 to April 2021, 17% dropped out. Based on the blind MoCA, 52% had cognitive impairment, and 25% were at risk of social isolation according to the Lubben social network scale. We observed that larger social networks were linked to better cognitive status and lower depression and anxiety levels, while loneliness was directly associated to depression severity. Older adults with cognitive impairment exhibited higher levels of depression and anxiety and were at greater risk for social isolation. In terms of the intervention, 91% preferred telephone over video calls. The intervention did not lead to improvements in cognitive or psychological scores. More work is needed to assess the utility of this intervention for the support of a heterogenous cross-cultural sample of older adults at-risk for social isolation, including individuals with cognitive impairment. Future research should explore longer intervention periods, categorize participants by call type, and target those meeting social isolation criteria. ClinicalTrials.gov NCT04480112.

Solving the issue of staffing shortage of medical staff using remote technologies and 3‑d interaction between students and the teacher at the RSBHI «Kirensk district hospital»

The topic of personnel shortage is close to all hospitals, relevant in all regions, both in central healthcare institutions and in the periphery. In September 2023, the RSBHI «Kirensk District Hospital» together with the RSBEI «Irkutsk Basic Medical College» launched a pilot project for distance learning in-person and part-time of mid-level medical personnel at the hospital. Target. Closing the personnel shortage. Formation of a personnel reserve in the institution. Results. Successful mastery of the curriculum by all students. Transfer of all students to the second year. Conclusion. Using our example, we would like to show the advantages of distance learning in-person and part-time of mid-level medical personnel, we are open to sharing experiences.

Efficient Loading into and Controlled Release of Lipophilic Compound from Liposomes by Using Cyclodextrin as Novel Trapping Agent.

Lipid bilayer vesicles, liposomes are representative drug delivery carriers. High encapsulation efficiency and release control of drugs are essential for clinical application of liposomes. For efficient drug loading into liposomes, remote loading method using driving force like transmembrane gradients of pH and ions are utilized. Ions are called as "trapping agents," which are also critical for the controlled release of drugs loaded into liposomes inside. It is difficult to apply ions as trapping agents to various drugs because of limited physicochemical compatibility between drugs and ions. Cyclodextrins (CDs) with hydrophobic cavity can make inclusion complexes with various hydrophobic compounds. Therefore, we aimed to evaluate the potential of CDs as a novel trapping agent using sulfobutylether-β-cyclodextrin (SBE-β-CD) and ibuprofen (IB), a weak acid hydrophobic drug. Encapsulation efficiency of IB in liposomes with pH gradient was approximately 27%, and it was enhanced by intraliposomal SBE-β-CD inclusion in addition to pH gradient, which was SBE-β-CD concentration-dependent. In liposomes with pH gradient, a large fraction of IB was released in a short time. This early-stage rapid IB release was significantly suppressed by the inclusion of SBE-β-CD inside liposomes. Thus, novel remote loading technology by intraliposomal SBE-β-CD enabled the efficient encapsulation of the hydrophobic drug into the aqueous phase of liposomes as well as their controlled release. This technology should be applied to various drugs that can be included into CDs in order to enhance their therapeutic benefits.

Effectiveness of Telemedicine and Remote Monitoring in Reducing Postpartum Hemorrhage Rates: A Meta-Analysis

Postpartum hemorrhage (PPH) is a leading cause of maternal morbidity and mortality worldwide, particularly in low- and middle-income countries (LMICs) with limited access to healthcare. Telemedicine and remote monitoring technologies offer potential solutions for early detection and management of PPH. This meta-analysis aimed to evaluate the effectiveness of these technologies in reducing PPH rates. A systematic search of PubMed, Embase, Cochrane Library, and Web of Science was conducted for studies published between 2013 and 2024 investigating the impact of telemedicine and remote monitoring interventions on PPH rates. Randomized controlled trials (RCTs) and observational studies with a control group were included. The primary outcome was the incidence of PPH (blood loss ≥500 ml after vaginal delivery or ≥1000 ml after cesarean delivery). Pooled risk ratios (RR) with 95% confidence intervals (CI) were calculated using a random-effects model. Publication bias was assessed using funnel plot asymmetry and Egger's test. Six studies involving 4200 women met the inclusion criteria. The pooled analysis demonstrated a statistically significant reduction in PPH rates in the intervention groups compared to the control groups (RR 0.56; 95% CI 0.47-0.67; p&lt;0.00001). The funnel plot was symmetrical, and Egger's test was not statistically significant (p=0.45), suggesting no evidence of publication bias. Telemedicine and remote monitoring interventions are associated with a significant reduction in PPH rates. These findings support the integration of these technologies into postpartum care to improve maternal outcomes, particularly in resource-constrained settings.

Boundary Layer Modelling of Flow Acceleration and Energy Transfer Effects in Smart Pavement Design

The integration of remote technology into the construction industry has advanced the emergence of smart, self-learning infrastructure across all levels of land transportation design and development. However, energy harvesting capabilities for smart road ventilation purposes have not yet been fully researched as the world gravitates towards energy sustainability. This study thus presents a mathematical investigation of the self-draining design potentials of road pavements, leveraging on energy absorption and conversion to accelerate conductive and convective ventilation of these pavements during wet conditions, as a means of ensuring the skid resistance and safety of such pavements are not compromised. Applying numerical methods with the aid of commercial software code MATLAB®, the classical physics of fluid-surface interaction was used to model accelerated drainage of microflood off paved surfaces through methodical modification of the thickness of the boundary layer associated with the flow regime over the flat road surface. Results indicate significant influences of energy exchange, thermal, and viscous diffusivity on flow acceleration. Alterations in parameters such as the slip factor, thermally induced Brownian motion or phoretic characteristics of the fluid particles at the boundary induce accelerated flow at the surface of the pavement. The findings contribute to the advancement of smart infrastructure by offering practical insights into the potential benefits of integrating energy-harvesting technologies into road pavement systems. By optimizing flow acceleration mechanisms, smart pavements can play a crucial role in improving road safety and sustainability in urban environments.

Dynamic analysis of a pedestrian bridge using monitoring and computational techniques

Soil-structure interaction (SSI) represents an important parameter when analyzing the dynamic behavior of bridges, considering the combined effects of soil, foundation, and structure to ensure an adequate structural representation. This paper applied a computational modeling strategy associated with soil-structure interaction methodology to represent the dynamic behavior of a timber-concrete pedestrian bridge of the Polytechnic School of the University of São Paulo. The computational models were validated and calibrated using monitoring results from an extensive structural health monitoring campaign. The bridge monitoring program was characterized using embedded sensors and remote monitoring technology: ground-based radar interferometry and video motion amplification. The instrumentation results were compared to establish the capabilities and advantages of this novel remote monitoring technique. The experimental results obtained from free and forced vibrations in the asset served as a basis for validating the developed computational model and allowed the evaluation of the asset behavior in service for different loading conditions. This paper emphasizes the importance of considering an SSI approach to represent the bridge dynamic behavior more accurately, enabling the use of more reliable numerical models to assess the bridge structural responses throughout its life-cycle.