Cognitive Computing and Internet of Things最新文献

{"title":"Exploring The Implementation of AI in a Cost-effective Device for Predicting Sleep Quality","authors":"Jing Peng Lee, Bruce Yu, Kenneth Y T Lim","doi":"10.54941/ahfe1003981","DOIUrl":"https://doi.org/10.54941/ahfe1003981","url":null,"abstract":"This report presents the development and effectiveness of an Arduino-based sleep tracking device that can accurately measure various parameters of sleep, including movement, temperature, sound, light intensity, and humidity. The device was designed to be low-cost and easy to use, while not compromising on its ability to accurately measure sleep activity. The effectiveness of the device was evaluated by collecting data from test subjects and comparing it to the data collected by other sleep tracking devices. The collected data was then processed and used to train Artificial Intelligence (AI) models such as Backward Propagation Neural Network, Linear Regression Model, and Grey Relation Analysis, to predict the sleep quality rating from 0% to 100% and to identify the main cause of poor sleep. The results of the study demonstrated that the Arduino-based sleep tracking device is an effective and cost-efficient tool for measuring various parameters of sleep. However, the pressure sensor may sometimes result in inaccurate readings, which can be addressed through data cleaning and filtering. Furthermore, the use of AI models was able to predict the sleep quality rating and identify the main causes of poor sleep with high accuracy. Further research is needed to evaluate the device's performance over a longer period of time and in a larger sample of participants.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124449373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attempt to develop analysis model of reader’s pictogram understanding process","authors":"Tatsuya Sakabe, Hiroaki Kosaka","doi":"10.54941/ahfe1003298","DOIUrl":"https://doi.org/10.54941/ahfe1003298","url":null,"abstract":"When designing pictograms, a pictogram designer decides the meaning intended to be conveyed by a pictogram. It is desirable that the reader understands the meaning of the pictogram as intended by the designer. However, there are readers who understand a pictogram very differently from the designer's intention. Due to this difference between the designer’s intention and these readers’ understanding, the pictogram communicates the wrong message to the readers. This difference should be minimized.We attempted to develop a model to analyze a reader’s pictogram comprehension process. Analyzing the reader's pictogram comprehension process will contribute to clarifying the causes of differences between readers’ understanding and designers’ intentions. The proposed model does not simulate the cognitive processes of the reader. Instead, it logically analyses the process from the pictogram that a reader reads as input to the phrases representing the pictogram described by the reader as output.First, we conducted an experiment in which subjects looked at pictograms and described what pictograms they saw. We collected pictogram comprehension data through the experiment. Second, on the basis of the collected data, we developed a model that analyzed the process of understanding for the pictograms used in the experiment.The proposed model consists of three procedures:1)Breaking down the pictogram that a reader reads into its elements such as human beings and objects.2)Analyzing the relationship between each element.3)Analyzing the relationship between how a reader actually reads and understands a pictogram and the pictogram's grammatical relationship.We believe that the model is useful for estimating in detail why readers understand pictograms the way they do.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115340183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Industry4.0 Tools: Integrated Building Site Payment Management Portal for Construction Works","authors":"L. Amusan, Terdoo Udendeh, C. Aigbavboa","doi":"10.54941/ahfe1001837","DOIUrl":"https://doi.org/10.54941/ahfe1001837","url":null,"abstract":"Management of construction site financial engagement is one of prerequisite of an effective site management. In recent times Building informatics concept has been useful in developing state of art equipment and process. In this study therefore, building informatics planning was generated that could be used for financial management purpose on site. The research was carried out using qualitative and quantitative research method, quantitative research method involved the use of structured questionnaire developed in Likert scale 1 to 5. Therefore with the aid of purposive sampling method, fifty (50) samples were picked using purposive sampling method. Construction professional constitute the nucleus of the respondents. The statistical inference was carried out on the data with Relative agreement Index and presented in tables. Qualitative method was used to develop the proposed integrated system. The study developed an integrated system that could assist in overcoming the negative vices of payment on site. The following task was carried out in line with aim of the study: identification of existing web-based financial platform, critical success factor in deployment of payment interface, methods of preventing financial conflict on site, challenges of web- interface, critical success factor in deployment of payment interface, identification of strengths and weaknesses of existing web-based financial platforms, among others. The interface can help solve basic problem about financial payment difficulty on site. The direction of choice should be in automating different aspect of building and construction for maximum productivity. The system that was developed in the context of this study can help prevent cost overrun on site, payment conflict, and delay payment among others.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"399 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116678055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive Weighted 3D Object Image Inference Model Based on Image Complexity","authors":"Yueqi Liu, Pu Meng, Zhuoyue Diao, Xin Meng, Liqun Zhang, Xiaodong Li","doi":"10.54941/ahfe1001832","DOIUrl":"https://doi.org/10.54941/ahfe1001832","url":null,"abstract":"The research on product style classification based on CNN is very active, but the data used to train CNN(Convolutional Neural Networks) are often single-view images of 3D objects, which will lead to the loss of unpredictable object feature information and does not match the real scene. It reduces the quality of the model training. This paper proposes an adaptive weighted CNN model based on image complexity. Feature extraction is performed on images of 3D objects from different perspectives through convolutional neural networks, and the final classification result is obtained by weighting based on image complexity. The 3D object discrimination model in this paper is more in line with the cognitive process of the audience, and can improve the quality of style inference of 3D objects.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126286190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accurate Stress detection from Novel Real-Time Electrodermal Activity Signals and Multi-task Learning Models","authors":"Stefan de Vries, R. Smits, Michalina Tataj, M. Ronckers, Mayra Van Der Pol, Fransje van Oost, E. Adam, H. Smaling, E. Meinders","doi":"10.54941/ahfe1001845","DOIUrl":"https://doi.org/10.54941/ahfe1001845","url":null,"abstract":"Stress often is associated with physical and mental health issues. To prevent these issues, an early detection of stress is essential. However, for people with an intellectual disability effectively expressing stress can be difficult and therefore, the necessary intervention can be delayed. An automatic stress detection system could help caregivers in early detection of stress development. This can be achieved using wearable sensors that continuously record physiology. The changes in physiological signals, like in skin conductance can be used to classify moments of stress. The devices recording these signals are however, not always suitable for long term measurements. The present study evaluates a newly developed sock integrated skin conductance sensor (SentiSock) that does not restrict movement and stays comfortable over time. To assess if the sensor can be used for stress detection a comparison was made with the Empatica E4, a commonly used wrist-based skin conductance sensor. Both sensors were worn by 28 participants (mean age 39.25 ± 17.04) in a lab study where stress was induced using mathematical exercises. The data was used to train a multitask learning neural network for each device, following an identical procedure. The models were validated using a 5-fold cross validation that resulted in an average balanced accuracy of 0.824 (SD = 0.018) for Empatica E4 and 0.834 (SD = 0.019) for SentiSock. This demonstrated that both sensors can be used to detect stress adequately in lab conditions. Given these results, SentiSock will be further investigated for long term measurements.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129809522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Acute Physical Exercise on Cognitive Performance","authors":"M. Schneeberger, M. Pszeida, M. Lenger, Lisa Heiler, H. Simi, D. Wallner, A. Weber, A. Almer, S. Russegger, L. Paletta","doi":"10.54941/ahfe1003978","DOIUrl":"https://doi.org/10.54941/ahfe1003978","url":null,"abstract":"Numerous studies have found that aerobic endurance exercise increases neural activation and reduces reaction times suggesting that acute bouts of exercise may selectively boost executive function performance involving inhibitory control and attention. The objective of the presented study was to understand the concrete impact of a “standardised incremental exercise test to exhaustion” on certain cognitive functions, such as, sustained attention, and flexibility in the reaction behaviour. The results of the intervention demonstrate that reactive resilience increased (p=.008**) and reaction time was reduced (p<.001***) under application of the Determination Test (DT). Nevertheless, the number of errors increased but not in a significant manner (p>.05). The results of the Psychomotor Vigilance Task (PVT) showed that the reaction times were significantly decreasing as well (p=.002**), however, the errors in terms of “false starts” were significantly increasing (p=.002**). This research study demonstrates that acute physical exercise had a measurable impact on the cognitive performance of the participants. In particular, the PVT reported a statistically significant detrimental impact that refers to changes in sustained attention.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125154515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of the Heart Rate Measurement Module in a Telemonitoring Device for First Responders Deployed in Extreme Environments","authors":"Tanja Boljanić, Matija Štrbac, J. Malešević, V. Kojić, N. Topalović, G. Bijelic, M. Kostic","doi":"10.54941/ahfe1001838","DOIUrl":"https://doi.org/10.54941/ahfe1001838","url":null,"abstract":"This paper presents results of the SIXTHSENSE project, a research and innovation action within the H2020 program, aiming to develop new methods for unobtrusive monitoring of first responders based on multimodal sensing. The goal is to determine Heart Rate signal from ECG recorded by a multi sensor smart patch in the specific conditions the first responders are facing on their deployments. In addition to the challenges commonly faced when processing ECG signals recorded by wearables in high intensity activities, the work presented tackles the issues of noise generated by active sensors collocated with the ECG electrodes. Furthermore, the ergonomic requirements of the targeted users, namely firefighters and mountain rescuers, imposed positioning the multi sensor smart patch on the user’s back, making the analysis of recorder ECG signal more challenging. Initial experiments were conducted to determine the optimal electrode position on the back for ECG recording, and the design of the patch that would allow robust measurement of the signals, while not impeding the user during intense physical activity.Analysis of different algorithms for ECG signal processing was performed, considering both the specific distortions for ECG signals recorded on the back, and the effects of active system modules on the acquisition, namely electrotactile stimulation and iontophoretic analyte extraction.The prosposed multi sensor patch design and processing algorithm are presented and demonstrated in experiments simulating relevant conditions for the application of interest.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"467 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123378435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards Immersive Skill Training for First Responders with Biosensor-based Assessment of Situation Awareness","authors":"Amir Dini, M. Schneeberger, M. Pszeida, Lisa Heiler, L. Paletta","doi":"10.54941/ahfe1003979","DOIUrl":"https://doi.org/10.54941/ahfe1003979","url":null,"abstract":"First responders engage highly stressful situations at the emergency site that may induce stress, fear, panic and a collapse of clear thinking (Putnam, 1995). However, their physiological and cognitive readiness is of highest importance to enable appropriate decision making (Frye & Wearing, 2014). A major aspect for keeping control of the situation is that first responders should always maintain situation awareness. Training of the first responders’ routines improves resilience towards stressors in severe hazard conditions. Advanced training of first responders, in particular, the use of VR environments for the training of situation awareness for stress-resilient decision-making behavior is one of the upcoming challenges of the near future.Methods A Virtual Reality environment was developed with a typical firefighter scenario to train and to evaluate the situation awareness (SA) of squad leaders. The operator has two major tasks, (i) searching for pocket of embers on the ground by using an infrared camera and whenever detected to call for a team member to work on it, (ii) to survey her team of 5 first responders for their visible presence as well as for their health condition and consequently to react in proper time instants whenever team members would be injured or disappear. The movement of the team members within a predefined skill-oriented territory is activated by an AI-driven method. A wearable multisensory-based non-invasive measurement suite is mounted on the operator including VR in-built eye-tracking, biosensors for cardiovascular, electrodermal and temperature data capture, to report by means of digital human factors analytics. From the sensor data stream we intend to deduce psychological constructs, such as, situation awareness, physiological strain, cognitive-emotional stress, and fatigue. A pilot study is planned with N=20 students, with pre- and post-study cognitive tests, such as, determination test (Schuhfried, 1987) and Psychomotor Vigilance Test (PVT; Dinges & Powell, 1985), as well as the Situation Awareness Rating Technique (SART; Taylor, 1990). From the SART we will research for to situation awareness-specific digital biomarkers by means of correlation analysis. This multi-tasking configuration will enable to measure (a) executive functions, such as, cognitive flexibility, and (b) level 1, 2 and 3 SA by gaze-driven virtual events, such as, viewing first responder avatars. Results: We will describe the system architecture as well as the features of the VR-based skill evaluation system (VR with eye-tracking, biosensors, treadmill, dashboard). Test users will move on a treadmill that triggers the VR-based experience accordingly, by means of a Cyberith Visualizer platform. Videos that were captured from the use of the platform and application of biosensors with eye tracking will demonstrate the usefulness for the evaluation of SA. We will report from a first usability study with feedback from friendly users. At the conference, w","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121573486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}