Ambient Intelligence on the Dance Floor

2010 ◽  
pp. 1720-1737
Author(s):  
Magy Seif El-Nasr ◽  
Athanasios V. Vasilakos
Keyword(s):  
Intelligent Systems ◽  
Physiological State ◽  
Pressure Sensors ◽  
Sensor Data ◽  
Layered Architecture ◽  
Performance Space ◽  
Art And Technology ◽  
Art Form ◽  
Ambient Intelligent ◽  
Physiological Sensors

With the evolution of intelligent devices, sensors, and ambient intelligent systems, it is not surprising to see many research projects starting to explore the design of intelligent artifacts in the area of art and technology; these projects take the form of art exhibits, interactive performances, and multi-media installations. In this paper, we seek to propose a new architecture for an ambient intelligent dance performance space. Dance is an art form that seeks to explore the use of gesture and body as means of artistic expression. This paper proposes an extension to the medium of expression currently used in dance—we seek to explore the use of the dance environment itself, including the stage lighting and music, as a medium for artistic reflection and expression. To materialize this vision, the performance space will be augmented with several sensors: physiological sensors worn by the dancers, as well as pressure sensor mats installed on the floor to track dancers’ movements. Data from these sensors will be passed into a three layered architecture: a layer analyzes sensor data collected from physiological and pressure sensors. Another layer intelligently adapts the lighting and music to portray the dancer’s physiological state given artistic patterns authored through specifically developed tools; and, lastly, a layer for presenting the music and lighting changes in the physical dance environment.

Ambient Intelligence on the Dance Floor

2011 ◽  
pp. 116-133
Author(s):  
Magy Seif El-Nasr ◽  
Athanasios V. Vasilakos
Keyword(s):  
Intelligent Systems ◽  
Physiological State ◽  
Pressure Sensors ◽  
Sensor Data ◽  
Layered Architecture ◽  
Performance Space ◽  
Art And Technology ◽  
Art Form ◽  
Ambient Intelligent ◽  
Physiological Sensors

With the evolution of intelligent devices, sensors, and ambient intelligent systems, it is not surprising to see many research projects starting to explore the design of intelligent artifacts in the area of art and technology; these projects take the form of art exhibits, interactive performances, and multi-media installations. In this paper, we seek to propose a new architecture for an ambient intelligent dance performance space. Dance is an art form that seeks to explore the use of gesture and body as means of artistic expression. This paper proposes an extension to the medium of expression currently used in dance—we seek to explore the use of the dance environment itself, including the stage lighting and music, as a medium for artistic reflection and expression. To materialize this vision, the performance space will be augmented with several sensors: physiological sensors worn by the dancers, as well as pressure sensor mats installed on the floor to track dancers’ movements. Data from these sensors will be passed into a three layered architecture: a layer analyzes sensor data collected from physiological and pressure sensors. Another layer intelligently adapts the lighting and music to portray the dancer’s physiological state given artistic patterns authored through specifically developed tools; and, lastly, a layer for presenting the music and lighting changes in the physical dance environment.

scholarly journals Tools for integrating inertial sensor data with video bio-loggers, including estimation of animal orientation, motion, and position

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
David E. Cade ◽  
William T. Gough ◽  
Max F. Czapanskiy ◽  
James A. Fahlbusch ◽  
Shirel R. Kahane-Rapport ◽  
...  
Keyword(s):  
Direct Observation ◽  
Inertial Sensor ◽  
Pressure Sensors ◽  
Sensor Data ◽  
Biological Research ◽  
Marine Realm ◽  
Spatial Coordinates ◽  
Measurement Units ◽  
Physiological Sensors

AbstractBio-logging devices equipped with inertial measurement units—particularly accelerometers, magnetometers, and pressure sensors—have revolutionized our ability to study animals as necessary electronics have gotten smaller and more affordable over the last two decades. These animal-attached tags allow for fine scale determination of behavior in the absence of direct observation, particularly useful in the marine realm, where direct observation is often impossible, and recent devices can integrate more power hungry and sensitive instruments, such as hydrophones, cameras, and physiological sensors. To convert the raw voltages recorded by bio-logging sensors into biologically meaningful metrics of orientation (e.g., pitch, roll and heading), motion (e.g., speed, specific acceleration) and position (e.g., depth and spatial coordinates), we developed a series of MATLAB tools and online instructional tutorials. Our tools are adaptable for a variety of devices, though we focus specifically on the integration of video, audio, 3-axis accelerometers, 3-axis magnetometers, 3-axis gyroscopes, pressure, temperature, light and GPS data that are the standard outputs from Customized Animal Tracking Solutions (CATS) video tags. Our tools were developed and tested on cetacean data but are designed to be modular and adaptable for a variety of marine and terrestrial species. In this text, we describe how to use these tools, the theories and ideas behind their development, and ideas and additional tools for applying the outputs of the process to biological research. We additionally explore and address common errors that can occur during processing and discuss future applications. All code is provided open source and is designed to be useful to both novice and experienced programmers.

Measurement of Mud Motor Back-Drive Dynamics, Associated Risks, and Benefits of Real-Time Detection and Mitigation Measures

2021 ◽  
pp. 1-19
Author(s):  
Junichi Sugiura ◽  
Steve Jones
Keyword(s):  
Rotation Speed ◽  
Pressure Sensors ◽  
Sensor Data ◽  
Depth Interval ◽  
Drill Bit ◽  
Motor Power ◽  
Stick Slip ◽  
Rate Of Penetration ◽  
The Past ◽  
Drive Dynamics

Summary North American shale drilling is a fast-paced environment where downhole drilling equipment is pushed to the limits for the maximum rate of penetration (ROP). Downhole mud motor power sections have rapidly advanced to deliver more horsepower and torque, resulting in different downhole dynamics that have not been identified in the past. High-frequency (HF) compact drilling dynamics recorders embedded in the drill bit, mud motor bit box, and motor top subassembly (top-sub) provide unique measurements to fully understand the reaction of the steerable-motor power section under load relative to the type of rock being drilled. Three-axis shock, gyro, and temperature sensors placed above and below the power section measure the dynamic response of power transfer to the bit and associated losses caused by back-drive dynamics. Detection of back-drive from surface measurements is not possible, and many measurement-while-drilling (MWD) systems do not have the measurement capability to identify the problem. Motor back-drive dynamics severity is dependent on many factors, including formation type, bit type, power section, weight on bit, and drillpipe size. The torsional energy stored and released in the drillstring can be high because of the interaction between surface rotation speed/torque output and mud motor downhole rotation speed/torque. Torsional drillstring energy wind-up and release results in variable power output at the bit, inconsistent rate of penetration, rapid fatigue on downhole equipment, and motor or drillstring backoffs and twistoffs. A new mechanism of motor back-drive dynamics caused by the use of an MWD pulser above a steerable motor has been discovered. HF continuous gyro sensors and pressure sensors were deployed to capture the mechanism in which a positive mud pulser reduces as much as one-third of the mud flow in the motor and bit rotation speed, creating a propensity for a bit to come to a complete stop in certain conditions and for the motor to rotate the drillstring backward. We have observed the backward rotation of a polycrystalline diamond compact (PDC) drill bit during severe stick-slip and back-drive events (−50 rev/min above the motor), confirming that the bit rotated backward for 9 milliseconds (ms) every 133.3 ms (at 7.5 Hz), using a 1,000-Hz continuous sampling/recording in-bit gyro. In one field test, multiple drillstring dynamics recorders were used to measure the motor back-drive severity along the drillstring. It was discovered that the back-drive dynamics are worse at the drillstring, approximately 1,110 ft behind the bit, than these measured at the motor top-sub position. These dynamics caused drillstring backoffs and twistoffs in a particular field. A motor back-drive mitigation tool was used in the field to compare the runs with and without the mitigation tool while keeping the surface drilling parameters nearly the same. The downhole drilling dynamics sensors were used to confirm that the mitigation tool significantly reduced stick-slip and eliminated the motor back-drive dynamics in the same depth interval. Detailed analysis of the HF embedded downhole sensor data provides an in-depth understanding of mud motor back-drive dynamics. The cause, severity, reduction in drilling performance and risk of incident can be identified, allowing performance and cost gains to be realized. This paper will detail the advantages to understanding and reducing motor back-drive dynamics, a topic that has not commonly been discussed in the past.

On Dependability Issues in Ambient Intelligence Systems

2011 ◽  
Vol 3 (3) ◽  
pp. 18-27
Author(s):  
Marcello Cinque ◽  
Antonio Coronato ◽  
Alessandro Testa
Keyword(s):  
Assisted Living ◽  
Intelligent Systems ◽  
Ambient Intelligence ◽  
Ambient Assisted Living ◽  
Smart Environments ◽  
Practical Application ◽  
Smart Systems ◽  
Computing Paradigm ◽  
Ambient Intelligent ◽  
Verification Techniques

Ambient Intelligence (AmI) is the emerging computing paradigm used to build next-generation smart environments. It provides services in a flexible, transparent, and anticipative manner, requiring minimal skills for human-computer interaction. Recently, AmI is being adapted to build smart systems to guide human activities in critical domains, such as, healthcare, ambient assisted living, and disaster recovery. However, the practical application to such domains generally calls for stringent dependability requirements, since the failure of even a single component may cause dangerous loss or hazard to people and machineries. Despite these concerns, there is still little understanding on dependability issues in Ambient Intelligent systems and on possible solutions. This paper provides an analysis of the AmI literature dealing with dependability issues and to propose an innovative architectural solution to such issues, based on the use of runtime verification techniques.

Internal and external factors effect on the mobile pressure sensors’ performance

Sensor Review ◽  
2016 ◽  
Vol 36 (4) ◽  
pp. 405-413 ◽  
Author(s):  
Semih Dalgin ◽  
Ahmet Özgür Dogru
Keyword(s):  
Pressure Sensor ◽  
Mobile Applications ◽  
Pressure Sensors ◽  
External Factors ◽  
Sensor Data ◽  
High Tech ◽  
Internal Factors ◽  
Content Type ◽  
Internal And External Factors ◽  
Mems Pressure Sensors

Purpose The purpose of this study is to investigate the effect of internal and external factors on the accuracy and consistency of the data provided by mobile-embedded micro-electromechanical system (MEMS) pressure sensors based on smartphones currently in use. Design/methodology/approach For this purpose, sensor type and smartphone model have been regarded as internal factors, whereas temperature, location and usage habits have been considered as external factors. These factors have been investigated by examining data sets provided by sensors from 14 different smartphones. In this context, internal factors have been analyzed by implementing accuracy assessment processes for three different smartphone models, whereas external factors have been evaluated by analyzing the line charts which present timely pressure changes. Findings The study outlined that the sensor data at different sources have different characteristics due to the affecting parameters. Even if the pressure sensors are used under similar circumstances, data of these sensors have inconsistencies because of the sensor drift originated by internal factors. This study concluded that it was not applicable to provide a common correction coefficient for pressure sensor data of each smartphone model. Therefore, relative data (pressure differences) should be taken into consideration rather than absolute data (pressure values) when developing mobile applications using sensor data. Research limitations/implications Results of this study can be used as the guideline for developing mobile applications using MEMS pressure sensors. One of the main finding of this paper is promoting the use of relative data (pressure differences) rather than absolute data (pressure values) when developing mobile applications using smartphone-embedded sensor data. This significant result was proved by examinations applied with in the study and can be applied by future research studies. Originality/value Existing studies mostly evaluate the use of MEMS pressure sensor data obtained from limited number of smartphone models. As each smartphone model has a specific technology, factors affecting the sensor performances should be identified and analyzed precisely in terms of smartphone models for providing extensive results. In this study, five smartphone models were used fractionally. In this context, they were used for examining the common effects of the factors, and detailed accuracy assessments were applied by using two high-tech smartphones in the market.

scholarly journals Exploring the Factors of Cooperation between Artists and Technologists in Creating New Media Art Works: Based on AHP

2020 ◽  
Vol 12 (19) ◽  
pp. 8049
Author(s):  
Min Li ◽  
Tsung-Chih Hsiao ◽  
Chih-Cheng Chen
Keyword(s):  
New Media ◽  
Media Art ◽  
New Media Art ◽  
Expert Opinions ◽  
Art And Technology ◽  
Art Form ◽  
Art Works ◽  
Collaboration Process ◽  
Influence Degree ◽  
Hierarchy Process

The deeper the combination of art and technology, the more extensive the cooperation between artists and technologists. In many cases, the creation of New Media Art requires the cooperation of artists and technologists. However, since New Media Art is an emerging art form, the process of cocreating New Media Art between the two is at the exploration stage. Especially in areas with underdeveloped New Media Art and underdeveloped technology, there exist many problems in the cooperation between the two, such as a lack of complete understanding of the factors involved in the cooperation process and a lack of reasonable planning for the cooperation process. Therefore, this study analyzes the factors that affect the collaboration process between the two creating New Media Art. Common factors are collected from the literature and then added or deleted after expert opinions. Then, analytical hierarchy process (AHP) method is applied to get the weight of each factor and understand the influence degree of the factor. The research results show that there are relatively fixed factors influencing the collaboration process between artists and technologists in creating New Media Art, and various factors have different degrees of influence on cooperation. Therefore, in the process of cooperation between the two parties, more emphasis should be placed on the factors of cooperation, which makes the cooperation more scientific.

scholarly journals Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4448 ◽  
Author(s):  
Günther Sagl ◽  
Bernd Resch ◽  
Andreas Petutschnig ◽  
Kalliopi Kyriakou ◽  
Michael Liedlgruber ◽  
...  
Keyword(s):  
Heart Rate ◽  
Galvanic Skin Response ◽  
Low Cost ◽  
Wearable Sensors ◽  
Sensor Data ◽  
Quantified Self ◽  
High Quality ◽  
Laboratory Equipment ◽  
Skin Response ◽  
Physiological Sensors

Wearable sensors are increasingly used in research, as well as for personal and private purposes. A variety of scientific studies are based on physiological measurements from such rather low-cost wearables. That said, how accurate are such measurements compared to measurements from well-calibrated, high-quality laboratory equipment used in psychological and medical research? The answer to this question, undoubtedly impacts the reliability of a study’s results. In this paper, we demonstrate an approach to quantify the accuracy of low-cost wearables in comparison to high-quality laboratory sensors. We therefore developed a benchmark framework for physiological sensors that covers the entire workflow from sensor data acquisition to the computation and interpretation of diverse correlation and similarity metrics. We evaluated this framework based on a study with 18 participants. Each participant was equipped with one high-quality laboratory sensor and two wearables. These three sensors simultaneously measured the physiological parameters such as heart rate and galvanic skin response, while the participant was cycling on an ergometer following a predefined routine. The results of our benchmarking show that cardiovascular parameters (heart rate, inter-beat interval, heart rate variability) yield very high correlations and similarities. Measurement of galvanic skin response, which is a more delicate undertaking, resulted in lower, but still reasonable correlations and similarities. We conclude that the benchmarked wearables provide physiological measurements such as heart rate and inter-beat interval with an accuracy close to that of the professional high-end sensor, but the accuracy varies more for other parameters, such as galvanic skin response.

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