... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks最新文献
Pub Date : 2020-01-01DOI: 10.5220/0009365401690176
M. Cagnetti, M. Leccisi, F. Leccese
A comparison between the most suitable routing protocols for WSNs applied in wide agriculture scenarios is shown. The protocols, already present in literature, have been conceived to better manage the power budget of the nodes and are particularly suitable to cover the energy issues that wide agriculture scenario can request. This study aims to indicate which of the protocols eligible for this scenario is the most suitable. Comparative simulation test will be shown.
{"title":"Reliability Comparison of Routing Protocols for WSNs in Wide Agriculture Scenarios by Means of ?L Index","authors":"M. Cagnetti, M. Leccisi, F. Leccese","doi":"10.5220/0009365401690176","DOIUrl":"https://doi.org/10.5220/0009365401690176","url":null,"abstract":"A comparison between the most suitable routing protocols for WSNs applied in wide agriculture scenarios is shown. The protocols, already present in literature, have been conceived to better manage the power budget of the nodes and are particularly suitable to cover the energy issues that wide agriculture scenario can request. This study aims to indicate which of the protocols eligible for this scenario is the most suitable. Comparative simulation test will be shown.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79517436","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}
Pub Date : 2020-01-01DOI: 10.5220/0008965800970104
S. Salehi, D. Stricker
This work validates the application of a low-cost inertial tracking suit, for strength exercise monitoring. The procedure includes an offline processing for body-IMU calibration and an online tracking and identification of lower body motion. We proposed an optimal movement pattern for the body-IMU calibration method from our previous work. Here, in order to reproduce real extreme situations, the focus is on the movements with high acceleration. For such movements, an optimal orientation tracking approach is introduced, which requires no accelerometer measurements and it thus minimizes error due to outliers. The online tracking algorithm is based on an extended Kalman filter(EKF), which estimates the position of upper and lower legs, along with hip and knee joint angles. This method applies the estimated values in the calibration process i.e. joint axes and positions, as well as biomechanical constraints of lower body. Therefore it requires no aiding sensors such as magnetometer. The algorithm is evaluated using optical tracker for two types of exercises: squat and hip abd/adduction which resulted average root mean square error(RMSE) of 9cm. Additionally, this work presents a personalized exercise identification approach, where an online template matching algorithm is applied and optimised using zero velocity crossing(ZVC) for feature extraction. This results reducing the execution time to 93% and improving the accuracy up to 33%.
{"title":"Validation of a Low-cost Inertial Exercise Tracker","authors":"S. Salehi, D. Stricker","doi":"10.5220/0008965800970104","DOIUrl":"https://doi.org/10.5220/0008965800970104","url":null,"abstract":"This work validates the application of a low-cost inertial tracking suit, for strength exercise monitoring. The procedure includes an offline processing for body-IMU calibration and an online tracking and identification of lower body motion. We proposed an optimal movement pattern for the body-IMU calibration method from our previous work. Here, in order to reproduce real extreme situations, the focus is on the movements with high acceleration. For such movements, an optimal orientation tracking approach is introduced, which requires no accelerometer measurements and it thus minimizes error due to outliers. The online tracking algorithm is based on an extended Kalman filter(EKF), which estimates the position of upper and lower legs, along with hip and knee joint angles. This method applies the estimated values in the calibration process i.e. joint axes and positions, as well as biomechanical constraints of lower body. Therefore it requires no aiding sensors such as magnetometer. The algorithm is evaluated using optical tracker for two types of exercises: squat and hip abd/adduction which resulted average root mean square error(RMSE) of 9cm. Additionally, this work presents a personalized exercise identification approach, where an online template matching algorithm is applied and optimised using zero velocity crossing(ZVC) for feature extraction. This results reducing the execution time to 93% and improving the accuracy up to 33%.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80058806","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}
Pub Date : 2020-01-01DOI: 10.5220/0009000601210128
C. Benavente-Peces, Nisrine Ibadah
Currently, most of the human activities impact the environment. Worldwide sustainable development is required to preserve a good quality of life. Energy efficiency is one of the most relevant issues that the scientific community and society must face along the next decades. This paper focuses on reviewing and noting the main factors which impact the optimization of electrical energy efficiency in Smart Buildings, including distribution, consumption analysis, strategies and management. Smart grids and smart buildings are playing a key role in the definition of the following generations of cities where the impact of energy consumption on the environment must be reduced as much as possible. Notwithstanding, all the factors impacting the production and distribution must be also taken into consideration by energy production companies and distribution companies as well. Green energies are being introduced in smart cities and buildings, only slower than required, and in general, focusing on the consumption side asking for higher performance monitoring and control techniques, and encouraging to incorporate energy harvesting initiatives to improve the overall efficiency. In this paper, the major target is pointing out all the relevant factors influencing smart building energy efficiency, up to the consumer side and, at the same time, paying attention on distribution and generation issues and, specifically, available communication standards, technologies, techniques, algorithms, which enable high performance systems to optimize energy consumption and occupant comfort.
{"title":"ICT Technologies, Techniques and Applications to Improve Energy Efficiency in Smart Buildings","authors":"C. Benavente-Peces, Nisrine Ibadah","doi":"10.5220/0009000601210128","DOIUrl":"https://doi.org/10.5220/0009000601210128","url":null,"abstract":"Currently, most of the human activities impact the environment. Worldwide sustainable development is required to preserve a good quality of life. Energy efficiency is one of the most relevant issues that the scientific community and society must face along the next decades. This paper focuses on reviewing and noting the main factors which impact the optimization of electrical energy efficiency in Smart Buildings, including distribution, consumption analysis, strategies and management. Smart grids and smart buildings are playing a key role in the definition of the following generations of cities where the impact of energy consumption on the environment must be reduced as much as possible. Notwithstanding, all the factors impacting the production and distribution must be also taken into consideration by energy production companies and distribution companies as well. Green energies are being introduced in smart cities and buildings, only slower than required, and in general, focusing on the consumption side asking for higher performance monitoring and control techniques, and encouraging to incorporate energy harvesting initiatives to improve the overall efficiency. In this paper, the major target is pointing out all the relevant factors influencing smart building energy efficiency, up to the consumer side and, at the same time, paying attention on distribution and generation issues and, specifically, available communication standards, technologies, techniques, algorithms, which enable high performance systems to optimize energy consumption and occupant comfort.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83006488","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}
Pub Date : 2020-01-01DOI: 10.5220/0009183301500156
Fadi T. El-Hassan
In emergency cases related to massive accidents, environme ntal disasters, and war time, health professionals face considerable challenges due to the high number of patie nts who are in need of emergency treatment. Research works attempt to propose effective in-hospital an d pre-hospital smart emergency systems to reduce the mortality rate among the patients who desperately wait t o receive appropriate care. This paper presents a model of a timely prehospital emergency management system that can be implemented as an interface to an Internet of Things (IoT) environment. This work presents the necessary stages for prehospital emergency environments, where many factors may make the timely manage ment of emergency systems very difficult. The proposed model is based on an Algorithmic State Machine ( ASM) that can be implemented in either hardware or software, providing an embedded system interfa c for IoT. Moreover, this paper provides a timing analysis for either a single emergency event or multiple sim ultaneous emergency events. Embedded systems’ developers can use the proposed model to produce an appropri ate ehospital smart emergency solution.
{"title":"Algorithmic State Machine Design for Timely Health Emergency Management in an IoT Environment","authors":"Fadi T. El-Hassan","doi":"10.5220/0009183301500156","DOIUrl":"https://doi.org/10.5220/0009183301500156","url":null,"abstract":"In emergency cases related to massive accidents, environme ntal disasters, and war time, health professionals face considerable challenges due to the high number of patie nts who are in need of emergency treatment. Research works attempt to propose effective in-hospital an d pre-hospital smart emergency systems to reduce the mortality rate among the patients who desperately wait t o receive appropriate care. This paper presents a model of a timely prehospital emergency management system that can be implemented as an interface to an Internet of Things (IoT) environment. This work presents the necessary stages for prehospital emergency environments, where many factors may make the timely manage ment of emergency systems very difficult. The proposed model is based on an Algorithmic State Machine ( ASM) that can be implemented in either hardware or software, providing an embedded system interfa c for IoT. Moreover, this paper provides a timing analysis for either a single emergency event or multiple sim ultaneous emergency events. Embedded systems’ developers can use the proposed model to produce an appropri ate ehospital smart emergency solution.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86129698","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}
Pub Date : 2020-01-01DOI: 10.5220/0008918600930096
D. Matatagui, I. Gràcia, M. C. Horrillo
Four surface acoustic waves (SAW) sensors based on sensitive layers of Fe2O3 nanoparticles, pure and combined with noble metals nanoparticles, composed an array sensor to measure ammonia in the environment. The sensor array was tested with nanostructured sensitive layers, which detected the changes of the elastic properties induced by ammonia interaction. The sensor with pure Fe2O3 nanoparticles exposed to 50 ppm of ammonia showed no significant effect, however the sensors with Fe2O3 nanoparticles combined with Au, Pt and Pd nanoparticles responded to these concentrations of this gas, which is so dangerous for the environment and the health, with a high sensitivity.
{"title":"Response of a SAW Sensor Array based on Nanoparticles for Measuring Ammonia in the Environment","authors":"D. Matatagui, I. Gràcia, M. C. Horrillo","doi":"10.5220/0008918600930096","DOIUrl":"https://doi.org/10.5220/0008918600930096","url":null,"abstract":"Four surface acoustic waves (SAW) sensors based on sensitive layers of Fe2O3 nanoparticles, pure and combined with noble metals nanoparticles, composed an array sensor to measure ammonia in the environment. The sensor array was tested with nanostructured sensitive layers, which detected the changes of the elastic properties induced by ammonia interaction. The sensor with pure Fe2O3 nanoparticles exposed to 50 ppm of ammonia showed no significant effect, however the sensors with Fe2O3 nanoparticles combined with Au, Pt and Pd nanoparticles responded to these concentrations of this gas, which is so dangerous for the environment and the health, with a high sensitivity.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79398935","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}
Pub Date : 2020-01-01DOI: 10.5220/0008957200290040
Avishek Mukherjee, Zhenghao Zhang
A reliable fall detection system has tremendous value to the well-being of seniors living alone. We design and implement MultiSense, a novel fall detection system, which has the following desirable features. First, it does not require the human to wear any device, therefore it is convenient to seniors. Second, it has been tested in typical settings including living room and bathroom, and has shown very good accuracy. Third, it is built with inexpensive components, with expected hardware cost around $150 to cover a typical room. Therefore, it has a key advantage over the current commercial fall detection systems which all require the human to wear some device, as well as over academic research prototypes which have various limitations such as lower accuracy. The high accuracy is achieved mainly by combining senses from multiple types of sensors that complement each other, which includes a motion sensor, a heat sensor, and a floor vibration sensor. As the activities that are difficult to classify for some sensors are often not difficult for others, combining the strength of multiple types of sensors brings the performance to a level that can meet the requirements in practice.
{"title":"MultiSense: A Highly Reliable Wearable-free Human Fall Detection Systems","authors":"Avishek Mukherjee, Zhenghao Zhang","doi":"10.5220/0008957200290040","DOIUrl":"https://doi.org/10.5220/0008957200290040","url":null,"abstract":"A reliable fall detection system has tremendous value to the well-being of seniors living alone. We design and implement MultiSense, a novel fall detection system, which has the following desirable features. First, it does not require the human to wear any device, therefore it is convenient to seniors. Second, it has been tested in typical settings including living room and bathroom, and has shown very good accuracy. Third, it is built with inexpensive components, with expected hardware cost around $150 to cover a typical room. Therefore, it has a key advantage over the current commercial fall detection systems which all require the human to wear some device, as well as over academic research prototypes which have various limitations such as lower accuracy. The high accuracy is achieved mainly by combining senses from multiple types of sensors that complement each other, which includes a motion sensor, a heat sensor, and a floor vibration sensor. As the activities that are difficult to classify for some sensors are often not difficult for others, combining the strength of multiple types of sensors brings the performance to a level that can meet the requirements in practice.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73334263","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}
Pub Date : 2020-01-01DOI: 10.5220/0009171100610068
A. Szczurek, M. Maciejewska, B. Bak, Jakub Wilk, J. Wilde, M. Siuda
Infestation of bee colony with Varroa destructor proceeds exponentially. It is important to detect the disease at its very early stage. However, the distinction of later infestation stages is also practical. We proposed to apply gas sensor array measurements of beehive air as the source of information which may be useful for this kind of assessment. Honeybee infestation was classified into three categories: ‘low’, ‘medium’ and ‘high’, two categories: ‘low’ and ‘medium to high’, and another two categories: ‘high’ and ‘medium to low’. Responses of gas sensor array to beehive air were used as the input data of the classifier, which was trained to distinguish the categories. The results of the analysis demonstrated that category ‘low’ was determined most effectively, with an error rate of about 10%. Category ‘high’ was most difficult to determine. In this case the lowest error rate was about 20%. Based on our analysis, the approach based on binary classification was favoured and SVM outperformed ensemble of classification trees. It was found, that first several minutes of gas sensors exposure to beehive air were sufficient to attain effective classification. The presented method of varroosis determination, based on beehive air sensing with gas sensors is innovative and has high potential of application in beekeeping.
{"title":"Classification of Honeybee Infestation by Varroa Destructor using Gas Sensor Array","authors":"A. Szczurek, M. Maciejewska, B. Bak, Jakub Wilk, J. Wilde, M. Siuda","doi":"10.5220/0009171100610068","DOIUrl":"https://doi.org/10.5220/0009171100610068","url":null,"abstract":"Infestation of bee colony with Varroa destructor proceeds exponentially. It is important to detect the disease at its very early stage. However, the distinction of later infestation stages is also practical. We proposed to apply gas sensor array measurements of beehive air as the source of information which may be useful for this kind of assessment. Honeybee infestation was classified into three categories: ‘low’, ‘medium’ and ‘high’, two categories: ‘low’ and ‘medium to high’, and another two categories: ‘high’ and ‘medium to low’. Responses of gas sensor array to beehive air were used as the input data of the classifier, which was trained to distinguish the categories. The results of the analysis demonstrated that category ‘low’ was determined most effectively, with an error rate of about 10%. Category ‘high’ was most difficult to determine. In this case the lowest error rate was about 20%. Based on our analysis, the approach based on binary classification was favoured and SVM outperformed ensemble of classification trees. It was found, that first several minutes of gas sensors exposure to beehive air were sufficient to attain effective classification. The presented method of varroosis determination, based on beehive air sensing with gas sensors is innovative and has high potential of application in beekeeping.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90738666","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}
Pub Date : 2020-01-01DOI: 10.5220/0008968400410051
T. Araújo, L. Silva, A. Moreira
: Atmospheric pressure sensors are important devices for several applications, including environment monitoring and indoor positioning tracking systems. This paper proposes a method to enhance the quality of data obtained from low-cost atmospheric pressure sensors using a machine learning algorithm to predict the error behaviour. By using the extremely Randomized Trees algorithm, a model was trained with a reference sensor data for temperature and humidity and with all low-cost sensor datasets that were co-located into an artificial climatic chamber that simulated different climatic situations. Fifteen low-cost environmental sensor units, composed by five different models, were considered. They measure – together – temperature, relative humidity and atmospheric pressure. In the evaluation, three categories of output metrics were considered: raw; trained by the independent sensor data; and trained by the low-cost sensor data. The model trained by the reference sensor was able to reduce the Mean Absolute Error (MAE) between atmospheric pressure sensor pairs by up to 67%, while the same ensemble trained with all low-cost data was able to reduce the MAE by up to 98%. These results suggest that low-cost environmental sensors can be a good asset if their data are properly processed.
{"title":"Deviation Prediction and Correction on Low-Cost Atmospheric Pressure Sensors using a Machine-Learning Algorithm","authors":"T. Araújo, L. Silva, A. Moreira","doi":"10.5220/0008968400410051","DOIUrl":"https://doi.org/10.5220/0008968400410051","url":null,"abstract":": Atmospheric pressure sensors are important devices for several applications, including environment monitoring and indoor positioning tracking systems. This paper proposes a method to enhance the quality of data obtained from low-cost atmospheric pressure sensors using a machine learning algorithm to predict the error behaviour. By using the extremely Randomized Trees algorithm, a model was trained with a reference sensor data for temperature and humidity and with all low-cost sensor datasets that were co-located into an artificial climatic chamber that simulated different climatic situations. Fifteen low-cost environmental sensor units, composed by five different models, were considered. They measure – together – temperature, relative humidity and atmospheric pressure. In the evaluation, three categories of output metrics were considered: raw; trained by the independent sensor data; and trained by the low-cost sensor data. The model trained by the reference sensor was able to reduce the Mean Absolute Error (MAE) between atmospheric pressure sensor pairs by up to 67%, while the same ensemble trained with all low-cost data was able to reduce the MAE by up to 98%. These results suggest that low-cost environmental sensors can be a good asset if their data are properly processed.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77520616","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}
Pub Date : 2020-01-01DOI: 10.5220/0009098701290135
Dimitri Kraft, R. Bader, G. Bieber
Natural and artificial joints of a human body are emitting vibration and sound during the movement. The sound and vibration pattern of a joint is characteristic and changes due to damage, uneven tread wear, injuries, or other influences. Hence, the vibration and sound analysis enables an estimation of the joint condition. This kind of analysis, vibroarthrography (VAG), allows the analysis of diseases like arthritis or osteoporosis and might determine trauma, inflammation, or misalignment. The classification of the vibration and sound data is very challenging and needs a comprehensive annotated data base. Current existing data bases are very limited and insufficient for deep learning or artificial intelligent approaches. In this paper, we describe a new concept of the design of a vibroarthrography system using a sensor network. We discuss the possible improvements and we give an outlook for the future work and application fields of VAG.
{"title":"Enhancing Vibroarthrography by using Sensor Fusion","authors":"Dimitri Kraft, R. Bader, G. Bieber","doi":"10.5220/0009098701290135","DOIUrl":"https://doi.org/10.5220/0009098701290135","url":null,"abstract":"Natural and artificial joints of a human body are emitting vibration and sound during the movement. The sound and vibration pattern of a joint is characteristic and changes due to damage, uneven tread wear, injuries, or other influences. Hence, the vibration and sound analysis enables an estimation of the joint condition. This kind of analysis, vibroarthrography (VAG), allows the analysis of diseases like arthritis or osteoporosis and might determine trauma, inflammation, or misalignment. The classification of the vibration and sound data is very challenging and needs a comprehensive annotated data base. Current existing data bases are very limited and insufficient for deep learning or artificial intelligent approaches. In this paper, we describe a new concept of the design of a vibroarthrography system using a sensor network. We discuss the possible improvements and we give an outlook for the future work and application fields of VAG.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74185375","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}
Pub Date : 2020-01-01DOI: 10.5220/0008987501130120
Nao Akayama, Daisaku Arita, Atsushi Shimada, R. Taniguchi
: Semi-automated sensing and visualization of conditions and activities in farm fields have been actively pursued in recent years. There are three types of agricultural information: sensor information, farm work information, and plant biological information. Measuring and visualizing these agricultural information can provide valuable support to farm managers. In this study, we focus on sensor information and farm work information and develop a web application named SALATA (Sharing and AccumuLating Agricultural TAcit knowledge) that collects and shares sensor information and farm work information collected in farm fields and correlates the information in time series. SALATA need to have intuitive operation and quick response in order that people of various ages will use it on a daily basis. Therefore, there are two primary pages: the main page for visualizing simple information quickly and the analytical page for visualizing multiple pieces of information on one page. Usability evaluation experiments are performed, showing that SALATA can be operated intuitively and respond quickly.
近年来，农业领域条件和活动的半自动化传感和可视化得到了积极的发展。农业信息有三种类型:传感器信息、农业工作信息和植物生物信息。测量和可视化这些农业信息可以为农场管理者提供有价值的支持。在本研究中，我们以传感器信息和农活信息为研究对象，开发了一个名为SALATA (Sharing and accumulation Agricultural TAcit knowledge)的web应用程序，用于收集和共享田间采集的传感器信息和农活信息，并将信息进行时间序列关联。SALATA需要有直观的操作和快速的反应，以便不同年龄的人每天都能使用它。因此，有两个主要页面:用于快速可视化简单信息的主页和用于在一个页面上可视化多个信息的分析页面。进行了可用性评估实验，结果表明SALATA操作直观，响应速度快。
{"title":"SALATA: A Web Application for Visualizing Sensor Information in Farm Fields","authors":"Nao Akayama, Daisaku Arita, Atsushi Shimada, R. Taniguchi","doi":"10.5220/0008987501130120","DOIUrl":"https://doi.org/10.5220/0008987501130120","url":null,"abstract":": Semi-automated sensing and visualization of conditions and activities in farm fields have been actively pursued in recent years. There are three types of agricultural information: sensor information, farm work information, and plant biological information. Measuring and visualizing these agricultural information can provide valuable support to farm managers. In this study, we focus on sensor information and farm work information and develop a web application named SALATA (Sharing and AccumuLating Agricultural TAcit knowledge) that collects and shares sensor information and farm work information collected in farm fields and correlates the information in time series. SALATA need to have intuitive operation and quick response in order that people of various ages will use it on a daily basis. Therefore, there are two primary pages: the main page for visualizing simple information quickly and the analytical page for visualizing multiple pieces of information on one page. Usability evaluation experiments are performed, showing that SALATA can be operated intuitively and respond quickly.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77327537","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}
... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks
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