Remote Collection Research Articles

Application of Key Technologies of Distributed Storage Based on the Internet of Things in Urban Fire Protection

Due to the rapid development of science and technology in the current era, fires occur more frequently, and the relationship between various economic activities and things is becoming more and more frequent. The need for real-time monitoring and remote monitoring of various firefighting facilities in buildings has become very urgent; this is a task that must be put on the agenda. The existing urban fire remote monitoring system has fewer intelligent networks, so it has high requirements for the firefighters on duty in the fire control room, which is no longer sufficient for the firefighting needs of the modern society. This paper proposes a wireless city fire remote monitoring system based on Internet of Things technology, NB-IoT technology, and cloud computing technology and studies core technologies such as designing wireless monitoring nodes at the perception layer. In the urban fire protection environment of distributed storage, several important theories, key technologies, and related algorithms are being studied in detail. After a variety of experimental verification results, the spatial data engine and adaptive spatial data model of the metadata database are developed. This provides a distributed storage virtual city geographic environment, multilevel, multiregional design and development of a simulated prototype platform and storage, management, sharing, and visualization of urban geospatial data. After technical analysis, a visualization framework was installed, which has the characteristics of global vector grid integration and distributed spatial data. Through the research on the key technology of distributed storage of the Internet of Things, this paper applies it to urban fire protection and promotes the intelligent development of urban fire protection. The application of IoT storage technology in urban fire protection can solve the shortcomings of the current urban fire remote monitoring system and automatic fire alarm system. Wireless city fire remote monitoring system, real-time collection, and transmission and storage of working status information of various fire facilities in the building are provided. The functions of real-time monitoring, real-time alarm, real-time search query, record query, maintenance management, route guidance, and user management are also realized.

Neurobehavioral Symptoms and Heart Rate Variability: Feasibility of Remote Collection Using Mobile Health Technology.

To determine the covariance of heart rate variability (HRV) and self-reported neurobehavioral symptoms after traumatic brain injury (TBI) collected using mobile health (mHealth) technology. Community. Adults with lifetime history of TBI (n = 52) and adults with no history of brain injury (n = 12). Two-week prospective ecological momentary assessment study. Behavioral Assessment Screening Tool (BASTmHealth) subscales (Negative Affect, Fatigue, Executive Dysfunction, Substance Abuse, and Impulsivity) measured frequency of neurobehavioral symptoms via a RedCap link sent by text message. Resting HRV (root mean square of successive R-R interval differences) was measured for 5 minutes every morning upon waking using a commercially available heart rate monitor (Polar H10, paired with Elite HRV app). Data for n = 48 (n = 38 with TBI; n = 10 without TBI) participants were included in covariance analyses, with average cross-correlation coefficients (0-day lag) varying greatly across participants. We found that the presence and direction of the relationship between HRV and neurobehavioral symptoms varied from person to person. Cross-correlation coefficients r ≤ -0.30, observed in 27.1% to 29.2% of participants for Negative Affect, Executive Dysfunction, and Fatigue, 22.9% of participants for Impulsivity, and only 10.4% of participants for Substance Abuse, supported our hypothesis that lower HRV would covary with more frequent symptoms. However, we also found 2.0% to 20.8% of participants had positive cross-correlations (r ≥ 0.30) across all subscales, indicating that higher HRV may sometimes correlate with more neurobehavioral symptoms, and 54.2% to 87.5% had no significant cross-correlations. It is generally feasible for community-dwelling adults with and without TBI to use a commercially available wearable device to capture daily HRV measures and to complete a short, electronic self-reported neurobehavioral symptom measure for a 2-week period. The covariance of HRV and neurobehavioral symptoms over time suggests that HRV could be used as a relevant physiological biomarker of neurobehavioral symptoms, though how it would be interpreted and used in practice would vary on a person-by-person and symptom domain basis and requires further study.

Social Adaptation of Students in a Multicultural Environment during Distance Learning

The problem of social adaptation of students in a multicultural environment has always been a concern of pedagogical science. With the development of telecommunication technologies, educational institutions face with the issue of finding effective forms of interaction between students. The aim of the article is to theoretically and empirically develop an integrated concept of studying the resilience of foreign students in a multicultural environment during distance learning. Methods: survey, methods of remote collection and processing of information (GOOGLE Forms), Self-Determination Test; K. Riff’s Scale of Psychological Well-Being, statistical methods of data processing, methods of analysis of the reliability of survey. The correlation between adaptation and resilience of foreign students who participated in the study is (r = 0.45; p <0.01). In turn, the resilience index is 81.92%. According to the study, students show high and medium rates of resilience during distance learning in the process of adaptation to a multicultural environment. It has been found that most students do not have difficulty adapting to distance learning due to the coronavirus pandemic (COVID-19). Thus, it was found that the process of adaptation of students in a multicultural environment during distance learning allowed maintaining a high rate of resilience, which indicates its effectiveness. Further research should be aimed at studying the development of professional competencies among students of narrow educational and professional training. It is also necessary to develop in detail the methodology for implementing the model of adaptation to distance learning.

Runet Users' Attitude to Outrageous Content in Virtual Social Environments

This study of the Runet virtual social environments deals with identifying and analyzing user reactions to watching a video clip containing outrageous behavior, and studying social attitudes of the respondents. The Celebrium-X platform employing the adjoint ideomotion technology for remote collection and processing of group neuro-responses was chosen as a research tool. As the empirical basis of the research, the raw data obtained as a result of the conducted survey was used. The results of the study have shown the respondents' negative attitude to publishing of outrageous video clips in virtual social environments. The Internet audience realizes a negative effect produced by the aggressive content on people's psychological sphere and social behavior.
 
 Received: 12 October 2021 / Accepted: 11 December 2021 / Published: 3 January 2022

Role of decentralized clinical trials in cancer drug development: Results from a survey of oncologists and patients.

As a result of the unprecedented challenges imposed by the COVID-19 pandemic on enrollment to cancer clinical trials, there has been an urgency to identify and incorporate new solutions to mitigate these difficulties. The concept of decentralized or hybrid clinical trials has rapidly gained currency, given that it aims to reduce patient burden, increase patient enrollment and retention, and preserve quality of life, while also increasing the efficiency of trial logistics. Therefore, the clinical trial environment is moving toward remote collection and assessment of data, transitioning from the classic site-centric model to one that is more patient-centric.

Архитектура централизованной системы удаленного сбора разнородной геофизической информации

The article analyses the features of the organization of centralized remote collection of heterogeneous geophysical information from the mine fields of mining enterprises. The authors have determined preferred architectural implementation of the collection system and analyzed its essential features affecting the reliability of functioning. Practical implementation experience of the system built within the framework of the proposed architecture, has been stated and summarized. Based on the operating experience, steps have been identified for its further development aimed at increasing its flexibility and reliability.

Long Term Results from Prospectively Collected Patient-Reported Outcomes in Hepatopancreatobiliary Surgery Using Mobile Health Technology within ERAS® Pathways

Introduction: Patient-reported outcomes (PROs) facilitate active patient engagement and compliance with therapeutic pathways. Mobile applications for the remote collection of PROs allows for ongoing patient education and the real-time aggregation of postoperative outcomes. We hypothesized this technology would improve patient outcomes and patient perceptions.

Alzheimer’s Disease Research and Outreach in the New Normal: Transitioning to the Virtual World

Following disruptions to research, clinical trials, and support for individuals with Alzheimer’s disease and related dementias (ADRD), 2020 taught us important lessons about the need for creativity, flexibility, and resourcefulness during an urgent and global public health crisis. The COVID-19 pandemic showed that we have knowledge and technology that can be rapidly implemented, adopted, and utilized by many sectors to allow the continued care and research of our older adult population with ADRD. Thus, this symposium will address virtual methods that are transforming ADRD research and support. First, Dr. Rhodus will discuss the implementation of online assessments in clinical trials at an Alzheimer’s Disease Research Center and the effects of sociodemographic disparities in online accessibility. Next, Dr. Bazzano will describe methods of remote collection of brain health data through tablets, smartphones, and wearables in the Bogalusa Heart Study. Then, Dr. Andersen will report on the transition from in-person to virtual assessments of cognitive and physical function in centenarian studies and address strategies for inclusivity of individuals with limited technology experience. Next, Dr. Fazio will introduce Project VITAL which aims to impact social isolation by increasing accessibility to virtual education and support for care community staff, family caregivers, and individuals with dementia. Finally, Dr. Penfold will report on the translation of a paper-based, face-to-face intervention for reducing caregiver burden into a self-directed online learning program. Overall, these presentations highlight successes and challenges in incorporating virtual-based methods to maintain engagement with participants, individuals with ADRD, and caregivers during the pandemic and beyond.

Lifetime optimization of dense wireless sensor networks using continuous ring-sector model

Wireless sensor networks (WSNs) are becoming increasingly utilized in applications that require remote collection of data on environmental conditions. In particular dense WSNs are emerging as an important sensing platforms for the Internet of Things (IoT). WSNs are able to generate huge volumes of raw data, which require network structuring and efficient collaboration between nodes to ensure efficient transmission. In order to reduce the amount of data carried in the network, data aggregation is used in WSNs to define a policy of data fusion and compression. In this paper, we investigate a model for data aggregation in a dense WSN with a single sink. The model divides a circular coverage region centered at the sink into patches which are intersections of sectors of concentric rings, and data in each patch is aggregated at a single node before transmission. Nodes only communicate with other nodes in the same sector. Based on these assumptions, we formulate a linear programming problem to maximize system lifetime by minimizing the maximum proportionate energy consumption over all nodes. Under a wide variety of conditions, the optimal solution employs two transmissions mechanisms: direct transmission, in which nodes send information directly to the sink; and stepwise transmission, in which nodes transmit information to adjacent nodes. An exact formula is given for the proportionate energy consumption rate of the network. Asymptotic forms of this exact solution are also derived, and are verified to agree with the linear programming solution. We investigate three strategies for improving system lifetime: nonuniform energy and information density; iterated compression; and modifications of rings. We conclude that iterated compression brings the greatest increase in system lifetime, but at the cost of possible information loss.

Blockchain-Enabled Online Diagnostic Platform of Suspected Patients of COVID-19 Like Pandemics

During times of pandemics, the healthcare system may collapse due to the high demand for healthcare resources. Hence, there is a need for an online-automated platform that enables remote collection of symptoms from suspected patients, accurate and fast diagnostics, and data sharing among different entities within the healthcare system. However, many privacy and scalability challenges face such a platform. To address such challenges, we propose a custom-designed blockchain enabled platform that guarantees privacy-preservation via a mixture of group signature and random numbers that support anonymity of suspected patients and unlinkability of data while enabling mutual interaction between the suspected patient and the platform; provides automatic diagnostics via a deep neural network-based detector that runs on a smart contract within the blockchain; and offers access and administrative authority of the healthcare entities to the database of symptoms and their diagnoses via a consortium-based blockchain architecture. Experimental studies demonstrate a detection accuracy of 90 percent based on a deep convolutional recurrent neural network. A case study of 500 expected patients is examined giving promising results. Every patient can know the test results after only 14 min of submitting the data. The storage requirements are as low as 0.52 MB for each suspected patient and 0.6 MB for each hospital.

Self-Powered Sensing for Smart Agriculture by Electromagnetic-Triboelectric Hybrid Generator.

The lack of efficient, low-cost, distributed energy collection methods is a vital factor restricting the application of the Internet of Things (IoT) in smart agriculture. This paper proposes a method based on triboelectric nanogenerator and electromagnetic generator to realize self-powered IoT nodes and self-powered sensors at the same time. An energy harvesting and sensing device based on electromagnetic-triboelectric hybrid generator (ES-ETHG) is designed. The peak power of ES-ETHG is 32.4 mW, which can supply power to IoT nodes for a long time with power management circuits. In addition, ES-ETHG can critically measure wind speed and wind level within the range of 3-15 m/s, and accurately detect wind direction within 2 s. Furthermore, the self-powered distributed weather sensing system based on ES-ETHG is developed to realize the remote collection of wind speed, wind direction, temperature, and humidity. This work proposes a solution for developing self-powered IoT and sensor in the field of smart agriculture.

Professional training of Economics students in higher educational institutions through the development of entrepreneurial climate

Professional economic education in Ukraine requires significant reforms because of thriving to integrate into the world economic space, which is impossible without the education of highly professional staff. The development of the entrepreneurial climate in the higher educational institution (HEI) by training the ability to work in a team and the general culture of doing business is an important task. It is specialized economic education that should lay the foundation for the dynamic economic development of the country. Methods used: survey, remote collection and processing of information (GOOGLE Forms), self-actualization test (SAT) (determining the level of general cultural competencies), study of value orientations (according to M. Rokych), methods of personal adaptation to a new professional environment (according to L.V. Yankovskyi), cultural and value orientations test (L.H. Pochebut). According to the study, students are convinced that entrepreneurial skills can be acquired. Students called self-organization the main competence for doing business. It was found that 50% of students have a low level of readiness for teamwork. Only 21% of respondents showed a high level of readiness for teamwork. It was found that special pedagogical conditions for creating an entrepreneurial climate can improve the level of higher economic education.

Efficiency of the project method in the development of professional competencies in future teachers

The objective is to study the effectiveness of the project method in the formation of professional competencies of future employees in the field of education. Methods: surveys and questionnaires, methods of remote collection and processing of information (GOOGLE Forms) the main methods used in the study were the method of questionnaires, the method of synthesis and analysis, the method of expert evaluations. The chi-square criterion, the feature combination criterion, and Pearson's correlation coefficient were used to calculate the results of the study. Results: The results of the study showed high indicators of the level of formation of students' subjectivity when using the project method in both the main and control groups. The introduction of the project method has an unconditional favourable effect in the process of forming the professional competencies of future teachers. Together with traditional teaching methods, the project method is an effective tool f or training future teachers. It is stated that the reliability of the obtained results is proved by the chi-square criterion. Its level is 0.01, on the basis of which it can be concluded that the proposed model is appropriate. Conclusion: Thus, after the analysis of the obtained results, the expediency of applying the project method in the training of future teachers was established.

The test-retest reliability of ride perception during treadmill and outdoor running

Subjective assessment of footwear experience during running is critical for recommendation and design. Recently, ride perception was quantified using an eight-dimension ratings scale. Ride varied by shoe and individual for treadmill running. However, it is unknown whether ride perception is a reliable measure in circumstances other than treadmill running and across sessions. The purpose of this study was to assess the intra-runner reliability of the previously developed ride rating 5-point semantic differential scale and the influence of surface on reliability ratings. We collected ride ratings in-person from nine runners in a controlled (lab) and semi-controlled (5 km outdoor paved path) environment and remotely from 177 runners in an uncontrolled collection. Post-run ride ratings were collected from each group following two separate running sessions on multiple surfaces using native shoes. We used intra-class correlation analysis to determine intra-runner reliability of ride ratings between separate runs in the same shoe on the same surface and in the same shoe on different surfaces. We used a reliability threshold of ≥0.70 as adequate. More than half of the in-person and slightly under half of the remote runners reached adequate reliability for the same surface runs. Reliability was lower for different surface runs for the remote runners but not the in-person runners. For in-person collection, firmness had adequate reliability during treadmill running, while awareness and sound level had good reliability outdoors. Weight and yield showed adequate and near adequate reliability for remote collections for same surface runs. Ride perception exhibits test-retest reliability in the assessment of subjective experience of footwear. Differences in ratings between surfaces indicate both the definition and construct of ride is captured with this subjective scale.

Highly versatile antibody binding assay for the detection of SARS-CoV-2 infection and vaccination

Monitoring the burden and spread of infection with the new coronavirus SARS-CoV-2, whether within small communities or in large geographical settings, is of paramount importance for public health purposes. Serology, which detects the host antibody response to the infection, is the most appropriate tool for this task, since virus-derived markers are most reliably detected during the acute phase of infection. Here we show that our ELISA protocol, which is based on antibody binding to the Receptor Binding Domain (RBD) of the S1 subunit of the viral Spike protein expressed as a novel fusion protein, detects antibody responses to SARS-CoV-2 infection and vaccination.We also show that our ELISA is accurate and versatile. It compares favorably with commercial assays widely used in clinical practice to determine exposure to SARS-CoV-2. Moreover, our protocol accommodates use of various blood- and non-blood-derived biospecimens, such as breast milk, as well as dried blood obtained with microsampling cartridges that are appropriate for remote collection. As a result, our RBD-based ELISA protocols are well suited for seroepidemiology and other large-scale studies requiring parsimonious sample collection outside of healthcare settings.

Remote Management of Patients after Total Joint Arthroplasty via a Web-Based Registry during the COVID-19 Pandemic.

Background: In 2020, due to the outbreak of the COVID-19 (Coronavirus Disease 2019) pandemic, patients who underwent total joint arthroplasty were not able to undergo the proper postoperative surgical and rehabilitative care. This study aims to evaluate the potential of a web-cloud-based database on patients’ follow-up in extraordinary situations, when a traditional in-person follow-up cannot be warranted. Methods: Patients who underwent joint arthroplasty at our Institute between 21 February and 16 March 2020 were included in the study group and were matched to a similar population undergoing joint arthroplasty in February/March 2019. All patients routinely complete questionnaires before and after treatment, including patient-reported outcome measures such as the Visual Analogues Scale (VAS), Knee/Hip Injury and Osteoarthritis Outcome Score Physical Function Short Form (KOOS-PS/HOOS-PS) and Short-Form Health Survey (SF-12) for the monitoring of clinical improvements. Results: 56 (study group) and 144 (control group) patients were included in the study. Both groups demonstrated significant improvements at 3 months. HOOS-PS improvement was significantly reduced in the 2020 group compared to 2019 (21.7 vs. 33.9, p < 0.001). This reduction was related to intense physical activities. Similarly, the functional score improvement related to these activities was reduced for patients undergoing knee replacement (8 vs. 10, p < 0.05). Conclusions: The web-based Institute Registry emerged as a meaningful and sensitive tool during an extraordinary situation such as the COVID-19 pandemic to monitor patients’ progression after total joint arthroplasties. Thanks to this tool, it was possible to observe that the prevention of usual postoperative care due to pandemic-related restrictions did not alter the benefits observed after joint replacement surgeries, even if this condition reduced the postoperative improvements in the most burdensome physical activities. A broader use of this kind of tool would improve and potentially reduce the burden and costs of postoperative patients’ monitoring in standard and extraordinary conditions. In addition, the systematic remote collection of data would allow for the identification of relevant differences in clinical outcomes in specific conditions or following the modification of treatment and rehabilitation protocols.

Changes in environmental epidemiology research methods due to COVID-19

BACKGROUND AND AIM: The obligatory pivot to digital research methods during the pandemic has illustrated its advantages in terms of flexibility, efficiency, broader geographic coverage, and lower barriers to participation. Digital research methods are likely to continue to expand in the post-COVID-19 era, although not without challenges and tradeoffs. The digital divide will become an increasingly complex source of selection bias, with important implications for participation of older individuals or those with lower socioeconomic position. For example, online questionnaires used heavily in the early stages of the pandemic, often had limited researcher control over who participated and little information on potentially large selection biases. METHODS: The pandemic has highlighted the potential of big data for public health protection. High-resolution geo-located data, increasingly available through either top-down (i.e. government surveillance) or bottom-up (i.e. volunteered geographic information) sources, paired with spatial analysis, are providing unprecedented opportunities to monitor complex phenomena such as human mobility and interactions. COVID-19 is proving an important impetus for new methods development to deal with complex spatio-temporal data structures with promising applications in environmental epidemiology. RESULTS:Research methods during COVID-19 shifted heavily towards remote biological sample collection, influencing the type and volume of samples collected. This shift is pushing development of improved analytical techniques for small volume samples. While remote collection offers several advantages over laboratory tests that could reduce selection bias (e.g. increased convenience and accessibility for participants living far from a lab), there are important challenges in ensuring data quality during the collection and handling of samples. CONCLUSIONS:In conclusion, the application of methods for conducting research that were a necessity during the COVID-19 pandemic because of the risk of infection can be expected to accelerate. The pandemic has triggered the development of creative, flexible research methods that offer advantages outside of the pandemic context; however, careful consideration of drawbacks is essential. KEYWORDS: COVID-19, big data, environmental epidemiology

Automated blood sampling in canine telemetry model: Enhanced assessment of immune liabilities

IntroductionThis manuscript presents a successful integration of multi-timepoint biomarker blood sampling (e.g., cytokines) in a conscious dog cardiovascular study using automated blood sampling via vascular access ports in telemetry instrumented dogs. In addition to determining plasma exposure of the test compound, the assessment of biomarkers of interest allows for more comprehensive preclinical evaluation on a traditional conscious dog cardiovascular (CV) telemetry study especially for immunology and immune-oncology molecules. This model system provides a rapid and efficient means to quickly gain understanding of potential effects on key cardiovascular parameters in large species that are commonly used for preclinical safety evaluations while collecting multiple blood samples for drug and cytokine analysis. MethodsMale beagle dogs were chronically implanted with telemetry devices (PhysioTel™ model D70-PCTP) and vascular access ports (SPMID-GRIDAC-5NC). BASi Culex-L automated blood sampling (ABS) (Bioanalytical Systems, Inc) system was used to collect blood samples at multiple time points for cytokine analysis. Four beagles received low-dose lipopolysaccharide solution (LPS) (0.1 and 0.5 μg/mL). The following cytokines were measured by Milliplex® map Canine Cytokine Magnetic Bead Panel: Interleukin (IL) 2, IL-6, IL-7, IL-8, IL-10, IL-15, IL-18, TNF-α, MCP-1, KC-like, GM-CSF, IFN gamma, and IP10. ResultsLow dose LPS administration induced a pronounced dose-dependent, transient release of key inflammatory cytokines (IL-2, IL-6, IL-10, TNF-α, MCP-1, and KC-like). Cytokine responses were similar to other canine and human endotoxin models. LPS administration led to an increase in body temperature, heart rate, and mean arterial pressure, as well as a decrease in QTcV interval. ConclusionSuccessful incorporation of cytokine analysis in telemetry instrumented dogs with vascular access ports allows for translational PK/PD modeling of both efficacy and safety of compounds in the immunology as well as the immune-oncology therapeutic areas designed to modulate the immune system. Remote collection of blood samples simultaneously with CV endpoints is a significant enhancement for assessment of biomarkers that are sensitive to animal handling and excitement associated with room disturbances which are obligatory with manual blood collection. Furthermore, implementing this approach has also refined our animal welfare procedure by reducing the handling during a study and thereby reducing stress (positive refinement 3R impact).

PO-1976 Has the Covid-19 Pandemic increased willingness to engage with remote collection of outcome data?

Purpose or Objective: Remote healthcare applications have been developing over many years, however clinical implementation has been cautious. As society has embraced technology during the Covid-19 pandemic, the question is: have attitudes towards remote healthcare technology also changed? One particular aspect of healthcare that could be addressed remotely is the collection of patient reported outcome measures (PROMs) using a digital voice assistant (DVA) such as the Amazon Echo (Alexa). This could improve both the frequency and quality of data collected. Materials and Methods: A questionnaire was developed to evaluate patient and carer opinions on using a DVA to report radiotherapy-related side effects. This was distributed to the adult patients in the radiotherapy department in February 2019 and to the Teenager, Young Adult and Paediatric radiotherapy department in mid 2019. It was redistributed in September 2020, allowing a pre/post Covid-19 comparison. To maximise engagement with the questionnaire, it was decided to ask a small number of simple questions. These four questions sought to ascertain whether the respondent was a patient or carer, respondent age (decade grouping), how knowledgeable they were about the Amazon Echo, and how willing they would be to participate in a hypothetical study in which they would use an Amazon Echo to record the side effects they experienced as a result of their cancer treatment. A comments box was included to allow participants to convey additional information. Results: 85 completed questionnaires were collected in 2019 and 43 in 2020. The median age of the initial survey cohort was 60-69 years old whilst for the second cohort was 50-59 years old. The slight difference in median age of the cohorts is likely a reflection on modifications to clinical practice due to Covid-19. 16% of the initial cohort and 19% of the second cohort were carers. 67% of the initial cohort responded that they had some or good knowledge of Amazon Echo, this increased to 84% in the second cohort (fig. 1). Willingness to participate was highest in the group of patients with good knowledge. 44% of the initial cohort were willing to take part in a study using an Amazon Echo to record side effects, increasing to 58% in the subsequent cohort (fig. 2). However, the percentage of respondents who were not willing to take part also increased from 32% to 37% with a reduction in the number of respondents who didn’t know (25% to 5%). Willingness to participate varied with age. Comments were diverse and included concerns about using technology and data security but also positive comments on the potential to reduce hospital visits. (Figure Presented) Conclusion: Overall, the survey results indicate an increased knowledge of DVA. There was also an increased willingness to engage with a DVA for remote collection of radiotherapy outcome data following the first wave of the Covid-19 pandemic.

Remote Sensing of Aerated Flows at Large Dams: Proof of Concept

Dams are important for flood mitigation, water supply, and hydroelectricity. Every dam has a water conveyance structure, such as a spillway, to safely release extreme floods when needed. The flows down spillways are often self-aerated and spillway design has typically been investigated in laboratory experiments, which is due to limitations in suitable full scale flow measurement instrumentation and safety considerations. Prototype measurements of aerated flows are urgently needed to quantify potential scale effects and to provide missing validation data for design guidelines and numerical simulations. Herein, an image-based analysis of free-surface flows on a stepped spillway was conducted from a top-view perspective at laboratory scale (fixed camera installation) and prototype scale (drone footage). The drone videos were obtained from citizen science data. Analyses allowed to remotely estimate the location of the inception point of free-surface aeration, air–water surface velocities, and their fluctuations, as well as the residual energy at the downstream end of the chute. The laboratory results were successfully validated against intrusive phase-detection probe data, while the prototype observations provided proof of concept at full scale. This study highlights the feasibility of image-based measurements at prototype spillways. It demonstrates how citizen science data can be used to advance our understanding of real world air–water flow processes and lays the foundations for the remote collection of long-missing prototype data.