Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9280694
S. Chen, Andrew Fishberg, Eyassu Shimelis, Joel Grimm, Scott van Broekhoven, Robert Shin, S. Karaman
Robotics competitions at the high school level attract a large number of students across the world. However, there is little emphasis on leveraging robotics to get middle school students excited about pursuing STEM education. In this paper, we describe a new program that targets middle school students in a local, four-week setting at the Massachusetts Institute of Technology (MIT). It aims to excite students by teaching the very basics of computer vision and robotics. The students program mini car-like robots, equipped with state-of-the-art computers, to navigate autonomously in a mock race track. We describe the hardware and software infrastructure that enables the program, the details of our curriculum, and the results of a short assessment. In addition, we describe four short programs, as well as a session where we teach high school teachers how to teach similar courses at their schools to their own students. The self-assessment indicates that the students feel more confident in programming and robotics after leaving the program, which we hope will enable them to pursue STEM education and robotics initiatives at school.
{"title":"A Hands-on Middle-School Robotics Software Program at MIT","authors":"S. Chen, Andrew Fishberg, Eyassu Shimelis, Joel Grimm, Scott van Broekhoven, Robert Shin, S. Karaman","doi":"10.1109/ISEC49744.2020.9280694","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9280694","url":null,"abstract":"Robotics competitions at the high school level attract a large number of students across the world. However, there is little emphasis on leveraging robotics to get middle school students excited about pursuing STEM education. In this paper, we describe a new program that targets middle school students in a local, four-week setting at the Massachusetts Institute of Technology (MIT). It aims to excite students by teaching the very basics of computer vision and robotics. The students program mini car-like robots, equipped with state-of-the-art computers, to navigate autonomously in a mock race track. We describe the hardware and software infrastructure that enables the program, the details of our curriculum, and the results of a short assessment. In addition, we describe four short programs, as well as a session where we teach high school teachers how to teach similar courses at their schools to their own students. The self-assessment indicates that the students feel more confident in programming and robotics after leaving the program, which we hope will enable them to pursue STEM education and robotics initiatives at school.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131621399","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 : 2020-08-01DOI: 10.1109/isec49744.2020.9280738
Sanish Rai
In computer science programming courses such as Java, C, Python, C++, the computer science (CS) lab plays the most significant role in helping freshmen students to learn the coding for the first time. In the labs, students work on some programming assignment problems and submit them on an online platform to be graded by instructors. The labs are designed to get students hands-on coding and implement the programs on the computer. Traditionally, the grading feedback is provided after a week or more, many of which are ignored by the students. As such, in this work, a one-on-one grading feedback methodology on completion of the program in the lab was conducted. Along with feedback, instructors would ask various questions to students related to the problem to understand their knowledge, thinking process and at the same time, enhance the communication skills of students. A quantitative study of the process using survey data showed that this method had a positive impact on students without causing any additional burden on instructors.
{"title":"Improving computer science lab feedback methods","authors":"Sanish Rai","doi":"10.1109/isec49744.2020.9280738","DOIUrl":"https://doi.org/10.1109/isec49744.2020.9280738","url":null,"abstract":"In computer science programming courses such as Java, C, Python, C++, the computer science (CS) lab plays the most significant role in helping freshmen students to learn the coding for the first time. In the labs, students work on some programming assignment problems and submit them on an online platform to be graded by instructors. The labs are designed to get students hands-on coding and implement the programs on the computer. Traditionally, the grading feedback is provided after a week or more, many of which are ignored by the students. As such, in this work, a one-on-one grading feedback methodology on completion of the program in the lab was conducted. Along with feedback, instructors would ask various questions to students related to the problem to understand their knowledge, thinking process and at the same time, enhance the communication skills of students. A quantitative study of the process using survey data showed that this method had a positive impact on students without causing any additional burden on instructors.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130210634","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 : 2020-08-01DOI: 10.1109/isec49744.2020.9397820
Sunrit Panda, Aditi Deshmukh, Gunjan Adya, Ali Ahmed
Currently, STEM education is a necessity for students at all levels. The iSTEM club represents a model for engaging and teaching students the necessary. Through excellent leadership, intensive programs to educate students, and opportunities to motivate students, the iSTEM club provides enhanced STEM education to students. With these methods, the iSTEM club has benefited the community through book drives, educational programs from elementary school students, and field trips to expand the student body’s knowledge. By participating in this club, students are able to reinforce knowledge with hands-on experiences and build up experience in order to perform well in society. As a result, the beneficial interaction between STEM clubs and STEM education structure is revealed.
{"title":"Edison High School iSTEM Club: A Model for Educational Excellence in STEM","authors":"Sunrit Panda, Aditi Deshmukh, Gunjan Adya, Ali Ahmed","doi":"10.1109/isec49744.2020.9397820","DOIUrl":"https://doi.org/10.1109/isec49744.2020.9397820","url":null,"abstract":"Currently, STEM education is a necessity for students at all levels. The iSTEM club represents a model for engaging and teaching students the necessary. Through excellent leadership, intensive programs to educate students, and opportunities to motivate students, the iSTEM club provides enhanced STEM education to students. With these methods, the iSTEM club has benefited the community through book drives, educational programs from elementary school students, and field trips to expand the student body’s knowledge. By participating in this club, students are able to reinforce knowledge with hands-on experiences and build up experience in order to perform well in society. As a result, the beneficial interaction between STEM clubs and STEM education structure is revealed.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"85 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132690663","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 : 2020-08-01DOI: 10.1109/ISEC49744.2020.9397849
S. Egodawela, H. Herath, R. Ranaweera, J. Wijayakulasooriya
Parents are always worried about the wellbeing of their children. As per the Statistics Report 2017 by Missing Children Europe Organization, a child is reported missing every 2 minutes. Due to the imminent threat, parents are prone to buy their children mobile phones to keep in touch with them. However, giving a Mobile phone to a child can cause issues including cyber bullying, improper use of social networks, access to mature age and illicit content on the internet and possibly, phone theft. As an effort to tackle some of those issues, this paper proposes a solution which enables parents to call, locate and track their children using a child-friendly mobile device. The common scenario the device would come to play is in enhancing the safety of a child who would travel alone on a typical route; for instance a child who walks from home to school and back. The device can be calibrated to keep track of a typical route of travel. Then, if the device detects some deviation from the usual route, it would trigger a notification to parents. A probability matrix based novel algorithm is introduced to detect route deviation. Design details of the mobile device, along with the details of the route deviation detection algorithm are presented in this paper.
{"title":"Device to Remotely Track and Locate the Position of a Child for Safety","authors":"S. Egodawela, H. Herath, R. Ranaweera, J. Wijayakulasooriya","doi":"10.1109/ISEC49744.2020.9397849","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9397849","url":null,"abstract":"Parents are always worried about the wellbeing of their children. As per the Statistics Report 2017 by Missing Children Europe Organization, a child is reported missing every 2 minutes. Due to the imminent threat, parents are prone to buy their children mobile phones to keep in touch with them. However, giving a Mobile phone to a child can cause issues including cyber bullying, improper use of social networks, access to mature age and illicit content on the internet and possibly, phone theft. As an effort to tackle some of those issues, this paper proposes a solution which enables parents to call, locate and track their children using a child-friendly mobile device. The common scenario the device would come to play is in enhancing the safety of a child who would travel alone on a typical route; for instance a child who walks from home to school and back. The device can be calibrated to keep track of a typical route of travel. Then, if the device detects some deviation from the usual route, it would trigger a notification to parents. A probability matrix based novel algorithm is introduced to detect route deviation. Design details of the mobile device, along with the details of the route deviation detection algorithm are presented in this paper.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128253646","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 : 2020-08-01DOI: 10.1109/isec49744.2020.9397814
Rehaam Siddiqui
With more people getting sick, it’s very important to understand what germs are and how they spread. A common way to determine where germs live is to take a piece of bread and wipe it on some surface, and then measure how quickly mold grows. While this experiment is commonly done, I wanted to extend this idea to see how well people understand where germs live. My poster includes some background information about germs and how to keep safe from getting sick. Since germs are too small to see, the bread experiment is a good way to easily see how quickly germs can grow. To Figure out who knows more about germs, I made a list of questions asking where germs are likely to be. First, I asked a group of adults where they thought germs are. I then asked my classmates (in first grade) what they thought. Then, by comparing the answers against real results that the moldy bread generates, I will answer the question of who knows more about germs: adults or first graders.
{"title":"Who knows more about germs? Adults or first graders?","authors":"Rehaam Siddiqui","doi":"10.1109/isec49744.2020.9397814","DOIUrl":"https://doi.org/10.1109/isec49744.2020.9397814","url":null,"abstract":"With more people getting sick, it’s very important to understand what germs are and how they spread. A common way to determine where germs live is to take a piece of bread and wipe it on some surface, and then measure how quickly mold grows. While this experiment is commonly done, I wanted to extend this idea to see how well people understand where germs live. My poster includes some background information about germs and how to keep safe from getting sick. Since germs are too small to see, the bread experiment is a good way to easily see how quickly germs can grow. To Figure out who knows more about germs, I made a list of questions asking where germs are likely to be. First, I asked a group of adults where they thought germs are. I then asked my classmates (in first grade) what they thought. Then, by comparing the answers against real results that the moldy bread generates, I will answer the question of who knows more about germs: adults or first graders.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134352507","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 : 2020-08-01DOI: 10.1109/ISEC49744.2020.9280639
Wei Yu
Project Based Learning (PBL) approach is known to motivate students to investigate and integrate knowledge of several domains to solve real-life problems. It drives students’ intrinsic curiosity to connect isolated concepts to optimize their learning outcomes. Taking the advantages of PBL, a ship storage room security system project was designed and implemented in a junior-level Electronics Lab course at our university. The purpose of the project was to help students to improve their understanding of electronic element characteristics and their abilities to interpret electronic diagrams, conFigure and operate of electronic equipment. During the project, students needed to (1) design an electronic diagram that is able to detect ship storage room door open/closed status, trigger an alarm system, and reset the alarm system, and then (2) build an integrated circuit on a breadboard by using various electronic elements following the electronic diagram. Students had to dig into different course contents instructed in class and at the same time learn other new knowledge from external resources, such as internet, industrial documents, etc, to combine them effectively to produce a practical solution. It has been observed that the project has successfully led the students to explore the underlying connections of a variety of electronic concepts from class and new knowledge from external resources reaching their increased understanding of electronics and overall course satisfaction. The student survey results indicate the project has demonstrated strong positive impacts on the improvement of their knowledge and skills in electronic elements, diagrams and equipment.
基于项目的学习(Project Based Learning, PBL)是一种激励学生调查和整合多个领域的知识来解决现实问题的方法。它激发了学生内在的好奇心，将孤立的概念联系起来，以优化他们的学习成果。利用PBL的优势，在我校电子学实验课上设计并实现了一个船舶库房安全系统方案。该项目的目的是帮助学生提高对电子元件特性的理解，以及对电子图表的理解，对电子设备的配置和操作的能力。在这个项目中，学生需要(1)设计一个能够检测船舶储藏室门的开/关状态、触发报警系统和复位报警系统的电子图，然后(2)根据电子图利用各种电子元件在breadboard上构建集成电路。学生必须深入研究课堂上讲授的不同课程内容，同时从外部资源(如互联网、行业文件等)中学习其他新知识，并将它们有效地结合起来，形成一个实用的解决方案。据观察，该项目成功地引导学生探索了课堂上各种电子概念和外部资源新知识之间的潜在联系，从而提高了他们对电子学的理解和整体课程满意度。学生调查结果表明，该项目对他们在电子元件、图表和设备方面的知识和技能的提高有很强的积极影响。
{"title":"A Hands-on Project to Improve Student Learning Experience in Electronics: Building Ship Storage Room Security System","authors":"Wei Yu","doi":"10.1109/ISEC49744.2020.9280639","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9280639","url":null,"abstract":"Project Based Learning (PBL) approach is known to motivate students to investigate and integrate knowledge of several domains to solve real-life problems. It drives students’ intrinsic curiosity to connect isolated concepts to optimize their learning outcomes. Taking the advantages of PBL, a ship storage room security system project was designed and implemented in a junior-level Electronics Lab course at our university. The purpose of the project was to help students to improve their understanding of electronic element characteristics and their abilities to interpret electronic diagrams, conFigure and operate of electronic equipment. During the project, students needed to (1) design an electronic diagram that is able to detect ship storage room door open/closed status, trigger an alarm system, and reset the alarm system, and then (2) build an integrated circuit on a breadboard by using various electronic elements following the electronic diagram. Students had to dig into different course contents instructed in class and at the same time learn other new knowledge from external resources, such as internet, industrial documents, etc, to combine them effectively to produce a practical solution. It has been observed that the project has successfully led the students to explore the underlying connections of a variety of electronic concepts from class and new knowledge from external resources reaching their increased understanding of electronics and overall course satisfaction. The student survey results indicate the project has demonstrated strong positive impacts on the improvement of their knowledge and skills in electronic elements, diagrams and equipment.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133398029","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 : 2020-08-01DOI: 10.1109/ISEC49744.2020.9397808
C. Pascale, Marian Rice, Shivay Sharma
NINo is a future DevOps / Data Science pipeline tool that is being developed by JHU APL and two ASPIRE interns. The goal of this capability is to expose function-level capabilities, via either a simple application or configuration file, for use in Docker [1], Serverless Architectures [2], or data science/analytic pipelines. The goal is similar to efforts such as Metaparticle [3] and Source-to-Image[4] that aim to lower the barrier to horizontal scaling of data processing and analysis capabilities. In previous years ASPIRE interns have developed tools to ease the acceptance of DevOps principles in JHU APL. They have created a web application, Harmonia, that asked users a few simple questions and supplied the scaffolding for a software project with artifacts to support sound software engineering processes. The lack of user interest has driven us to a more focused objective. NINo will focus on easing deployment to cloud environments. Ideally, any person could develop cloud-based data science services. The team and its work has been organized in an asynchronous and agile manner. There have been three members working on three subsystems: configuration, framework/integration, and artifact generation. An incremental and prototype-driven approach has allowed for creation of increasingly more functional software as internship has proceeded. Interns have been given extensive control over their development processes and have investigated the programming frameworks used. While the initial stages have not resulted in a complete system, the interns have improved their programming skills and complete common coding challenges. The team is close to integration testing and initial demonstration. As the academic year closes, team members will work on design improvement, refactoring, and generation of future feature requests from prospective users. One summer intern will focus on developing a user interface for configuring and observing results.
{"title":"Nanoservice Infrastructure Notation (NINo) and the ASPIRE Interns","authors":"C. Pascale, Marian Rice, Shivay Sharma","doi":"10.1109/ISEC49744.2020.9397808","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9397808","url":null,"abstract":"NINo is a future DevOps / Data Science pipeline tool that is being developed by JHU APL and two ASPIRE interns. The goal of this capability is to expose function-level capabilities, via either a simple application or configuration file, for use in Docker [1], Serverless Architectures [2], or data science/analytic pipelines. The goal is similar to efforts such as Metaparticle [3] and Source-to-Image[4] that aim to lower the barrier to horizontal scaling of data processing and analysis capabilities. In previous years ASPIRE interns have developed tools to ease the acceptance of DevOps principles in JHU APL. They have created a web application, Harmonia, that asked users a few simple questions and supplied the scaffolding for a software project with artifacts to support sound software engineering processes. The lack of user interest has driven us to a more focused objective. NINo will focus on easing deployment to cloud environments. Ideally, any person could develop cloud-based data science services. The team and its work has been organized in an asynchronous and agile manner. There have been three members working on three subsystems: configuration, framework/integration, and artifact generation. An incremental and prototype-driven approach has allowed for creation of increasingly more functional software as internship has proceeded. Interns have been given extensive control over their development processes and have investigated the programming frameworks used. While the initial stages have not resulted in a complete system, the interns have improved their programming skills and complete common coding challenges. The team is close to integration testing and initial demonstration. As the academic year closes, team members will work on design improvement, refactoring, and generation of future feature requests from prospective users. One summer intern will focus on developing a user interface for configuring and observing results.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121757686","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 : 2020-08-01DOI: 10.1109/isec49744.2020.9397840
Neo Cheng
I play the cello, but my intonation is not good because I do not always remember where to place my fingers on the strings. Usually I use a tuner to help me find the right spots, and then I put stickers to mark the locations. However, I always ask myself: What makes these locations the right spots for the right pitches? Can I prove it mathematically? In this project, I want to know the sticker locations using math only, without a tuner. First, I used my tuner to determine where to press the string for C, C#, D, D#, E, F, F#, G, G#, A, A#, B, and C. Next, I measured the pressed string length with a tape ruler. Then I calculated the pressed string length ratio to the whole string. For math, I knew there are 12 half-notes within an octave and the length is halved (50%) for each octave. I just needed to find a multiplier that divides the length between 100% and 50% equally. In other words, I needed to find a number M such that M*M*M*M*M*M*M*M*M*M*M* M=0.5. By using a scientific calculator, I found the magic number, M, to be 0.944! This means that for each half-note, the string needs to be reduced to 94.4%, and for each whole-note, the string needs to be reduced to 89.1%.
{"title":"The Relationship between Musical Scale, Cello String Length, and Math","authors":"Neo Cheng","doi":"10.1109/isec49744.2020.9397840","DOIUrl":"https://doi.org/10.1109/isec49744.2020.9397840","url":null,"abstract":"I play the cello, but my intonation is not good because I do not always remember where to place my fingers on the strings. Usually I use a tuner to help me find the right spots, and then I put stickers to mark the locations. However, I always ask myself: What makes these locations the right spots for the right pitches? Can I prove it mathematically? In this project, I want to know the sticker locations using math only, without a tuner. First, I used my tuner to determine where to press the string for C, C#, D, D#, E, F, F#, G, G#, A, A#, B, and C. Next, I measured the pressed string length with a tape ruler. Then I calculated the pressed string length ratio to the whole string. For math, I knew there are 12 half-notes within an octave and the length is halved (50%) for each octave. I just needed to find a multiplier that divides the length between 100% and 50% equally. In other words, I needed to find a number M such that M*M*M*M*M*M*M*M*M*M*M* M=0.5. By using a scientific calculator, I found the magic number, M, to be 0.944! This means that for each half-note, the string needs to be reduced to 94.4%, and for each whole-note, the string needs to be reduced to 89.1%.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122301745","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 : 2020-08-01DOI: 10.1109/ISEC49744.2020.9280746
Trinity Cheng
Free, widely-available smartphone-based sound level meters have been utilized to collect large quantities of distributed data in short time periods for the efficient creation of crowd-sourced noise maps. However, the accuracy of these apps can vary greatly as previous studies have shown. In this study, four smartphone-based sound level meters were tested to evaluate their agreement. Four experiments were conducted to test the impact of different apps, operating systems, smartphone hardware, and microphones on app measurements at different sound levels. A combination of four apps, four smartphones, two operating systems, and two microphone types were used in the tests, as well as a hardware-based sound level meter. Errors were evaluated based on two evaluation methods— root mean square error and linearity. The experiment results show that all of the apps produced different readings with respect to the same input stimulus. In other words, each of the apps, operating systems, smartphone hardware, and external microphones influenced the accuracy of smartphone-based sound level meters. Due to the wide variation in measurements, the usage of uncalibrated smartphone-based sound level meters seems to be unacceptable for serious noise assessments. However, the high linearity displayed by some apps indicates the potential for increased accuracy through calibration by professional-grade instruments.
{"title":"Evaluation of Smartphone-based Sound Level Meters","authors":"Trinity Cheng","doi":"10.1109/ISEC49744.2020.9280746","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9280746","url":null,"abstract":"Free, widely-available smartphone-based sound level meters have been utilized to collect large quantities of distributed data in short time periods for the efficient creation of crowd-sourced noise maps. However, the accuracy of these apps can vary greatly as previous studies have shown. In this study, four smartphone-based sound level meters were tested to evaluate their agreement. Four experiments were conducted to test the impact of different apps, operating systems, smartphone hardware, and microphones on app measurements at different sound levels. A combination of four apps, four smartphones, two operating systems, and two microphone types were used in the tests, as well as a hardware-based sound level meter. Errors were evaluated based on two evaluation methods— root mean square error and linearity. The experiment results show that all of the apps produced different readings with respect to the same input stimulus. In other words, each of the apps, operating systems, smartphone hardware, and external microphones influenced the accuracy of smartphone-based sound level meters. Due to the wide variation in measurements, the usage of uncalibrated smartphone-based sound level meters seems to be unacceptable for serious noise assessments. However, the high linearity displayed by some apps indicates the potential for increased accuracy through calibration by professional-grade instruments.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129037224","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 : 2020-08-01DOI: 10.1109/isec49744.2020.9397856
Riya J. Roy
My project is about building a prototype of a futuristic kitchen assistant that is powered by Artificial Intelligence and Robotics. Using Cozmo (an AI-powered robot made by Anki) and Calypso (a language developed by Professor David Touretzky at Carnegie Mellon University for programming intelligent robots), I have built a proof-of-concept futuristic kitchen assistant that shows how the food identification and serving process can be automated. I accomplished this by learning Calypso’s rule-based language and its five fundamental laws of computation. Using Calypso’s various programming features such as perception, teleoperation, pursue and consume, conflict resolution, speech and hearing, landmark-based navigation, and path planning, I learned how to make Cozmo move around and do intelligent activities, which are demonstrated in my prototype. I designed a model kitchen using a cardboard box. I used the wall templates that had special symbols called “ArUco markers” to help Cozmo recognize kitchen walls and door openings and plan his path accordingly. Once I had the physical model of the kitchen ready, I created a new Calypso program that simulated the model kitchen along with the walls, door openings, the Cozmo robot, and three cubes that represented three different types of food. The program enabled Cozmo to recognize my voice instructions to get a particular food, go to the kitchen through the door opening, pick up the cube that represented the correct food, bring it to the dining room, and then drop it on a plate in front of me. I faced several challenges such as how to make Cozmo recognize my voice, identify the door openings correctly, and move around without hitting obstacles. Eventually, after a lot of testing and debugging, I was able to get the kitchen assistant working and was able to prove that using a robot programming language such as Calypso, a robot can be programmed to perform highly complicated tasks such as listening to voice commands from human beings, navigate from one room to another (i.e., from the dining room to the kitchen), pick up an object (i.e., food), and then navigate and bring the object to another room (i.e., from the kitchen back to the dining room). In the future, I plan to add more intelligence to the kitchen assistant such as providing the ability for a person to select a dish/recipe on a smartphone app, making the kitchen assistant go to the kitchen, find the right ingredients, follow the instructions in the recipe, make the food, and then serve it to the person.
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