Pub Date : 2023-03-18DOI: 10.5121/csit.2023.130517
Kevin Hu, Yu Sun, Yujia Zhang
Recent years have witnessed the dramatic popularity of online music streaming and the use of headphones likeAirPods, which millions of people use daily [1]. Melodic EQ was inspired by these users to create the best audiolistening experience for listeners with various preferences [2]. Melodic EQ is a project that creates customEQs tothe user's custom music tastes and filters the audio to fit their favorite settings. To achieve this goal, the processstarts with a song file taken from an existing file, for example, Spotify downloads or mp3s. This file is then uploadedto the app. The software sorts the song in a genre detecting Algorithm and assigns a genre label to that song. Insidethe app, the user will create or select EQs for that genre and apply it to their music. The interface is easy to use andthe app aims to make everyone's preferences achievable and on the fly. That’s why there are presets for eachcategory for users who are unfamiliar with equalizers, and custom settings for advanced users to create their perfect sound for each genre.
{"title":"A Fully Automated Music Equalizer based on Music Genre Detection using Deep Learning and Neural Network","authors":"Kevin Hu, Yu Sun, Yujia Zhang","doi":"10.5121/csit.2023.130517","DOIUrl":"https://doi.org/10.5121/csit.2023.130517","url":null,"abstract":"Recent years have witnessed the dramatic popularity of online music streaming and the use of headphones likeAirPods, which millions of people use daily [1]. Melodic EQ was inspired by these users to create the best audiolistening experience for listeners with various preferences [2]. Melodic EQ is a project that creates customEQs tothe user's custom music tastes and filters the audio to fit their favorite settings. To achieve this goal, the processstarts with a song file taken from an existing file, for example, Spotify downloads or mp3s. This file is then uploadedto the app. The software sorts the song in a genre detecting Algorithm and assigns a genre label to that song. Insidethe app, the user will create or select EQs for that genre and apply it to their music. The interface is easy to use andthe app aims to make everyone's preferences achievable and on the fly. That’s why there are presets for eachcategory for users who are unfamiliar with equalizers, and custom settings for advanced users to create their perfect sound for each genre.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123748492","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 : 2023-03-18DOI: 10.5121/csit.2023.130515
Qingbo Wang
This paper considers the problem of real-time estimating the moving target acceleration in frequency modulated continuous wave (FMCW) radar. Based on the accelerated target FMCW radar echo signal model, after utilizing KeyStone transform to eliminate the ef ect of range migration on the signal parameters estimation. An improved fractional Fourier transform (FrFT) and optimized the best matching rotation angle search strategy is proposed to estimate the chirp rate of doppler dimension echosignal related to the target acceleration. Compared with the traditional FrFT, the approach in this paper has less computation and significantly reduced processing time while ensuring estimation accuracy. The proposed method is demonstrated with simulation and measurement data.
{"title":"An FrFT Based Real-Time Estimation of Moving Target Acceleration Method for FMCW Radar","authors":"Qingbo Wang","doi":"10.5121/csit.2023.130515","DOIUrl":"https://doi.org/10.5121/csit.2023.130515","url":null,"abstract":"This paper considers the problem of real-time estimating the moving target acceleration in frequency modulated continuous wave (FMCW) radar. Based on the accelerated target FMCW radar echo signal model, after utilizing KeyStone transform to eliminate the ef ect of range migration on the signal parameters estimation. An improved fractional Fourier transform (FrFT) and optimized the best matching rotation angle search strategy is proposed to estimate the chirp rate of doppler dimension echosignal related to the target acceleration. Compared with the traditional FrFT, the approach in this paper has less computation and significantly reduced processing time while ensuring estimation accuracy. The proposed method is demonstrated with simulation and measurement data.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122612664","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 : 2023-03-18DOI: 10.5121/csit.2023.130516
Yi-ru Wang, Yu Sun
Ever since the start of Figure Skating, there has been an emphasis on skating technique, especially in the step sequences of a skater’s choreography [1]. But Figure Skaters often are not able to detect the motion, edge, or placement of their blade on the ice without watching themselves skate. The solution to this problem would be to have a skate analyzer. A skate analyzer would record the movements of a skate on ice and one would be able to playback the recorded data and view their skate motion precisely [2]. Three main components that my project links together are the QTPY-ESP 32 microcontroller, the sensor that combines the accelerometer, gyroscope, and magnetometer, and the SD card reader. The QTPY-ESP32 is a microcontroller that acts as a main computer controlling the whole board. The QTPY is then connected to a sensor board through an I2c protocol. Then, through an SPI protocol, the QTPY is connected to an SD card reader. After the skater is finished recording, they can insert the SD card in a computer, upload the data into the app, and play it back. There is also a slider on the top of the screen that the skater can slide back and forth to view the skate at specific times in the file. This would be a great technology to use for skaters as they can playback their movements on ice and improve their technique [3].
{"title":"An Intelligent and Data-Based Skate Analyzer to Assist in Analyzing Movements of Skate on Ice","authors":"Yi-ru Wang, Yu Sun","doi":"10.5121/csit.2023.130516","DOIUrl":"https://doi.org/10.5121/csit.2023.130516","url":null,"abstract":"Ever since the start of Figure Skating, there has been an emphasis on skating technique, especially in the step sequences of a skater’s choreography [1]. But Figure Skaters often are not able to detect the motion, edge, or placement of their blade on the ice without watching themselves skate. The solution to this problem would be to have a skate analyzer. A skate analyzer would record the movements of a skate on ice and one would be able to playback the recorded data and view their skate motion precisely [2]. Three main components that my project links together are the QTPY-ESP 32 microcontroller, the sensor that combines the accelerometer, gyroscope, and magnetometer, and the SD card reader. The QTPY-ESP32 is a microcontroller that acts as a main computer controlling the whole board. The QTPY is then connected to a sensor board through an I2c protocol. Then, through an SPI protocol, the QTPY is connected to an SD card reader. After the skater is finished recording, they can insert the SD card in a computer, upload the data into the app, and play it back. There is also a slider on the top of the screen that the skater can slide back and forth to view the skate at specific times in the file. This would be a great technology to use for skaters as they can playback their movements on ice and improve their technique [3].","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125818720","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 : 2023-03-18DOI: 10.5121/csit.2023.130503
C. Zheng, Yu Sun, Yujia Zhang
For decades, mental illness has been a popular topic of discussion that still lingers for effective treatments [1]. While current therapy of mental disorders can achieve success, it is far from enough to prevent their occurrence and impacts on individuals [2]. Because of this, mental illness is an area of study that requires professionals and specialists to take a further step. Additionally, as the use of technology advances in the current society, young children and preteens gradually become victims of mental disorders as well: a community that often needs careful attention from adults and caregivers [3]. This paper introduces a method of treating mental disorders in young individuals that is not considered rare, but often overlooked, by many. This application encourages creativity and interests in its users, motivating them to actively engage on their strengths and use it to reflect their struggles.
{"title":"An Interactive and Collaborative Gaming Platform to Engage the Autism Spectrum in Art Learning using Artificial Intelligence","authors":"C. Zheng, Yu Sun, Yujia Zhang","doi":"10.5121/csit.2023.130503","DOIUrl":"https://doi.org/10.5121/csit.2023.130503","url":null,"abstract":"For decades, mental illness has been a popular topic of discussion that still lingers for effective treatments [1]. While current therapy of mental disorders can achieve success, it is far from enough to prevent their occurrence and impacts on individuals [2]. Because of this, mental illness is an area of study that requires professionals and specialists to take a further step. Additionally, as the use of technology advances in the current society, young children and preteens gradually become victims of mental disorders as well: a community that often needs careful attention from adults and caregivers [3]. This paper introduces a method of treating mental disorders in young individuals that is not considered rare, but often overlooked, by many. This application encourages creativity and interests in its users, motivating them to actively engage on their strengths and use it to reflect their struggles.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127529823","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 : 2023-03-18DOI: 10.5121/csit.2023.130511
Johnny Xu, John Morris
Video game designers often find themselves at a crossroad when designing levels; namely, many have a difficult time balancing the amount of control they want to have over what their levels look like [1]. If too little control is given, like in the case of pure perlin-noise generation, levels can end up with too much variation and unideal generations [2]. Softlock is an example of unideal generation in the case of metroidvania games, if the placement of keys cannot be easily controlled and end up being placed behind gates, the players can get permanently stuck [3]. Developers may usually hand-make all levels in order to try and prevent this from happening, however they risk spending too much effort and time on designing levels, resulting in a general lack of quantity in levels. Objectively speaking, both methods have their strengths and work well in specific genres of games, but limiting oneself to the boundaries of these methods does not fundamentally achieve both quantity and accuracy. This paper proposes an unique solution to this dilemma, providing automated generation of levels while also giving developers much more control over the overall output. Our method uses Answer Set Programming (ASP) to verify generation based on restrictions we place, guaranteeing the outcome to be what we want [4]. To demonstrate our method, we applied our solution to a 2D metroidvania game made in the Unity game engine and conducted quantitative tests to assess how well our method works as a level generator [5].
{"title":"Procedural Generation in 2D Metroidvania Game with Answer Set Programming","authors":"Johnny Xu, John Morris","doi":"10.5121/csit.2023.130511","DOIUrl":"https://doi.org/10.5121/csit.2023.130511","url":null,"abstract":"Video game designers often find themselves at a crossroad when designing levels; namely, many have a difficult time balancing the amount of control they want to have over what their levels look like [1]. If too little control is given, like in the case of pure perlin-noise generation, levels can end up with too much variation and unideal generations [2]. Softlock is an example of unideal generation in the case of metroidvania games, if the placement of keys cannot be easily controlled and end up being placed behind gates, the players can get permanently stuck [3]. Developers may usually hand-make all levels in order to try and prevent this from happening, however they risk spending too much effort and time on designing levels, resulting in a general lack of quantity in levels. Objectively speaking, both methods have their strengths and work well in specific genres of games, but limiting oneself to the boundaries of these methods does not fundamentally achieve both quantity and accuracy. This paper proposes an unique solution to this dilemma, providing automated generation of levels while also giving developers much more control over the overall output. Our method uses Answer Set Programming (ASP) to verify generation based on restrictions we place, guaranteeing the outcome to be what we want [4]. To demonstrate our method, we applied our solution to a 2D metroidvania game made in the Unity game engine and conducted quantitative tests to assess how well our method works as a level generator [5].","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133531571","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 : 2023-03-18DOI: 10.5121/csit.2023.130520
Chun Kit Fu, Yu Sun
Hosts are often desperate to find ways to rent their house, However, most of them do not have possess theknowledge of knowing what type of image cover would grasp the attention of their customer. Gilded by these needs, I have designed an application that uses machine learning to find the relationship between the images andtheirrating [1]. I first used JSON to convert the HTML file resource to a format where we can use in python for webscraping [2]. This paper designs an application tool to find all the object or characters inside images by webscraping and changes it into a model for machine learning [3]. Applied our application to predict the ratingandconducted a qualitative evaluation of the approach. In order to prove our result, I imported an image fromAirbnband found its rating. It turns out that the predicted rating is extremely close to the real rating, Proving The system’susability.
{"title":"Airbnb Research: An Analysis in Nexus BetweenVisual Description and Product Rating","authors":"Chun Kit Fu, Yu Sun","doi":"10.5121/csit.2023.130520","DOIUrl":"https://doi.org/10.5121/csit.2023.130520","url":null,"abstract":"Hosts are often desperate to find ways to rent their house, However, most of them do not have possess theknowledge of knowing what type of image cover would grasp the attention of their customer. Gilded by these needs, I have designed an application that uses machine learning to find the relationship between the images andtheirrating [1]. I first used JSON to convert the HTML file resource to a format where we can use in python for webscraping [2]. This paper designs an application tool to find all the object or characters inside images by webscraping and changes it into a model for machine learning [3]. Applied our application to predict the ratingandconducted a qualitative evaluation of the approach. In order to prove our result, I imported an image fromAirbnband found its rating. It turns out that the predicted rating is extremely close to the real rating, Proving The system’susability.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133565095","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 : 2023-03-18DOI: 10.5121/csit.2023.130506
Sunny Zhao, Ang Li
As the exchange between natural language and program code gradually becomes the need of industry, more and more interpreters and translators are required. Such natural language interpreters and converters can benefit society in a variety of fields, such as service industry, communication industry, and engineering industry [6]. Concise and accurate language processors will greatly boost the productivity of bottom repetitive works, provide examples and inspirations for students and industry workers, and become the tendency of the future. This paper introduces an application using natural language processing and neural network to effectively interpret and translate English to Python code, and detailly present the structural flow of the application [7]. This paper will also introduce the structure of the neural network, its validity, and how the python torch was applied and integrated. Furthermore, it will demonstrate the application and limitation of this model as well as its future improvements. We applied our application to educational needs and conducted qualitative evaluation of the approach. The result shows a beneficial and potential effect that is applicable to a greater field.
{"title":"An Natural Language Processed Web Application that Interpret and Convert English to Python Code","authors":"Sunny Zhao, Ang Li","doi":"10.5121/csit.2023.130506","DOIUrl":"https://doi.org/10.5121/csit.2023.130506","url":null,"abstract":"As the exchange between natural language and program code gradually becomes the need of industry, more and more interpreters and translators are required. Such natural language interpreters and converters can benefit society in a variety of fields, such as service industry, communication industry, and engineering industry [6]. Concise and accurate language processors will greatly boost the productivity of bottom repetitive works, provide examples and inspirations for students and industry workers, and become the tendency of the future. This paper introduces an application using natural language processing and neural network to effectively interpret and translate English to Python code, and detailly present the structural flow of the application [7]. This paper will also introduce the structure of the neural network, its validity, and how the python torch was applied and integrated. Furthermore, it will demonstrate the application and limitation of this model as well as its future improvements. We applied our application to educational needs and conducted qualitative evaluation of the approach. The result shows a beneficial and potential effect that is applicable to a greater field.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114615418","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 : 2023-03-18DOI: 10.5121/csit.2023.130504
Fahad Alsifiany
Drone terrorism may seem elementary and efforts in its mitigation may seem painless. The fact is that security bodies in many countries are still grappling with this growing security concern. The autonomous nature of drones and the unpredictable nature of drone attacks remain to be some of the unforeseen challenges undermining the mitigation efforts in combating drone terrorism. The need to upskill our security forces and the general public on the operational practices and security capabilities in the drone world cannot be overemphasized. This paper explores a futuristic solution to the current challenges encountered in the war against drone terrorism. In its design, it delves into the possibility of utilizing Artificial Intelligence (AI) in characterizing the features of drones identified in our airspace to determine their authenticity. It further enriches the employees of the security services and the general public with information on combating drone terrorism by benefiting from the accumulated experiences of the relevant and specialized affiliates
{"title":"Use of AI to Diversify and Improve the Performance of RF Sensors Drone Detection Mechanism","authors":"Fahad Alsifiany","doi":"10.5121/csit.2023.130504","DOIUrl":"https://doi.org/10.5121/csit.2023.130504","url":null,"abstract":"Drone terrorism may seem elementary and efforts in its mitigation may seem painless. The fact is that security bodies in many countries are still grappling with this growing security concern. The autonomous nature of drones and the unpredictable nature of drone attacks remain to be some of the unforeseen challenges undermining the mitigation efforts in combating drone terrorism. The need to upskill our security forces and the general public on the operational practices and security capabilities in the drone world cannot be overemphasized. This paper explores a futuristic solution to the current challenges encountered in the war against drone terrorism. In its design, it delves into the possibility of utilizing Artificial Intelligence (AI) in characterizing the features of drones identified in our airspace to determine their authenticity. It further enriches the employees of the security services and the general public with information on combating drone terrorism by benefiting from the accumulated experiences of the relevant and specialized affiliates","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121871075","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 : 2023-03-18DOI: 10.5121/csit.2023.130507
Kurt A. Vedros, Georgios Michail Makrakis, C. Kolias, Robert C. Ivans, C. Rieger
Embedded devices are omnipresent in modern networks, including those facilitating missioncritical applications. However, due to their constrained nature, novel mechanisms are required to provide external, and non-intrusive defenses. Among such approaches, one that has gained traction is based on analyzing the emanated electromagnetic (EM) signals. Unfortunately, one of the most neglected challenges of this approach is the manual gathering and fingerprinting of the corresponding EM signals. Indeed, even simple programs are comprised of numerous branches, making the fingerprinting stage extremely timeconsuming, and requiring the manual labor of an expert. To address this issue, we propose a framework for generating synthetic EM signals directly from machine code. These subsequent signals can be used to train an anomaly detection system. The advantage of this approach is that it completely removes the need for an elaborate and error-prone fingerprinting stage, thus, increasing the scalability of the protection mechanisms. The experimental evaluations indicate that our method provides above 90% detection accuracy against code injection attacks. Moreover, the proposed methodology inflicts only -1.3% penalty in accuracy for detecting injections of as little as four malicious instructions when compared to the same methods of training on real signals.
{"title":"Towards Scalable Anomaly Detection for Embedded Devices through Synthetic EM Fingerprinting","authors":"Kurt A. Vedros, Georgios Michail Makrakis, C. Kolias, Robert C. Ivans, C. Rieger","doi":"10.5121/csit.2023.130507","DOIUrl":"https://doi.org/10.5121/csit.2023.130507","url":null,"abstract":"Embedded devices are omnipresent in modern networks, including those facilitating missioncritical applications. However, due to their constrained nature, novel mechanisms are required to provide external, and non-intrusive defenses. Among such approaches, one that has gained traction is based on analyzing the emanated electromagnetic (EM) signals. Unfortunately, one of the most neglected challenges of this approach is the manual gathering and fingerprinting of the corresponding EM signals. Indeed, even simple programs are comprised of numerous branches, making the fingerprinting stage extremely timeconsuming, and requiring the manual labor of an expert. To address this issue, we propose a framework for generating synthetic EM signals directly from machine code. These subsequent signals can be used to train an anomaly detection system. The advantage of this approach is that it completely removes the need for an elaborate and error-prone fingerprinting stage, thus, increasing the scalability of the protection mechanisms. The experimental evaluations indicate that our method provides above 90% detection accuracy against code injection attacks. Moreover, the proposed methodology inflicts only -1.3% penalty in accuracy for detecting injections of as little as four malicious instructions when compared to the same methods of training on real signals.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126200159","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 : 2023-03-18DOI: 10.5121/csit.2023.130508
Lingshan Kong, Jonathan Sahagun
Currently, smart home systems have developed rapidly and really convenience people’s lives [1]. However, by focusing on the shutter and curtain in a smart home system, shutters can only move on manually, and shutter used less because the curtain is easy to control [2]. In order to try to fix these questions on shutter, we designed an application and hardware integrated system which can control the shutter automatically depending on light and temperature, and also can allow users to control their online shutters devices remotely. Besides, we used the firebase database to store the device's data and status, so that devices can be more memorable and smart in controlling the shutter even if the weather conditions affect the logic decision. We applied our application to some window shutters at home and conducted a qualitative evaluation of the approach. The results show that the system can make the decision based on the software logic and eventually control the shutter under different light and temperature conditions in order to have the best balance between sunlight and home light [3].
{"title":"An Smart Auto Shutter Controlling System for Intelligent Home based on Database Analyzing and Mechanical Devices","authors":"Lingshan Kong, Jonathan Sahagun","doi":"10.5121/csit.2023.130508","DOIUrl":"https://doi.org/10.5121/csit.2023.130508","url":null,"abstract":"Currently, smart home systems have developed rapidly and really convenience people’s lives [1]. However, by focusing on the shutter and curtain in a smart home system, shutters can only move on manually, and shutter used less because the curtain is easy to control [2]. In order to try to fix these questions on shutter, we designed an application and hardware integrated system which can control the shutter automatically depending on light and temperature, and also can allow users to control their online shutters devices remotely. Besides, we used the firebase database to store the device's data and status, so that devices can be more memorable and smart in controlling the shutter even if the weather conditions affect the logic decision. We applied our application to some window shutters at home and conducted a qualitative evaluation of the approach. The results show that the system can make the decision based on the software logic and eventually control the shutter under different light and temperature conditions in order to have the best balance between sunlight and home light [3].","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129917179","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：