M. Hito, Logan Kuo, A. Newman, Marysia Serafin, Sarah Yang, G. Lewin
{"title":"用于家庭安全装置的便携式z波信号检测器的研制","authors":"M. Hito, Logan Kuo, A. Newman, Marysia Serafin, Sarah Yang, G. Lewin","doi":"10.1109/SIEDS.2019.8735588","DOIUrl":null,"url":null,"abstract":"Many home automation systems use the wireless protocol Z-Wave for communication between devices in the network. Installers of such systems often face issues related to Z-Wave connectivity during installations, as devices must be placed so that Z-Wave signal strength between them is strong enough to add the device to the mesh network. The goal of this project is to design and prototype a device that measures Z-Wave signal strength to aid installers in the process of placing devices and troubleshooting device connectivity. While devices that measure Z-Wave signal strength currently exist, they are not optimized for installer use. Some devices require a proprietary license to operate, and some such as spectrum analyzers are expensive and have a large learning curve. The design's hardware consists of an antenna, software-defined radio (SDR), Raspberry Pi, LED array, activation button, battery, and housing. The antenna captures a modulated signal in the Z-Wave band and converts it to a voltage signal to be processed by the SDR. The voltage signal goes through an analog to digital converter in the SDR and is streamed into the Raspberry Pi as discrete voltage samples over time. The Raspberry Pi utilizes firmware called LibAirspy to interface to the SDR and forwards the voltage samples over time to a Python program, which then processes the data via downsampling, multiplication by the conjugate, and conversion to a decibel scale. The program finds the maximum power level measured over the interval and compared to a strength threshold. Whether the threshold has been met is displayed via LEDs on the tool. This tool will be used to decrease the resource intensivity of installing Z-Wave devices, leading to increased installer efficiency and lower call-center workload.","PeriodicalId":265421,"journal":{"name":"2019 Systems and Information Engineering Design Symposium (SIEDS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of a Portable Z-Wave Signal Detector for Home Security Installations\",\"authors\":\"M. Hito, Logan Kuo, A. Newman, Marysia Serafin, Sarah Yang, G. Lewin\",\"doi\":\"10.1109/SIEDS.2019.8735588\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many home automation systems use the wireless protocol Z-Wave for communication between devices in the network. Installers of such systems often face issues related to Z-Wave connectivity during installations, as devices must be placed so that Z-Wave signal strength between them is strong enough to add the device to the mesh network. The goal of this project is to design and prototype a device that measures Z-Wave signal strength to aid installers in the process of placing devices and troubleshooting device connectivity. While devices that measure Z-Wave signal strength currently exist, they are not optimized for installer use. Some devices require a proprietary license to operate, and some such as spectrum analyzers are expensive and have a large learning curve. The design's hardware consists of an antenna, software-defined radio (SDR), Raspberry Pi, LED array, activation button, battery, and housing. The antenna captures a modulated signal in the Z-Wave band and converts it to a voltage signal to be processed by the SDR. The voltage signal goes through an analog to digital converter in the SDR and is streamed into the Raspberry Pi as discrete voltage samples over time. The Raspberry Pi utilizes firmware called LibAirspy to interface to the SDR and forwards the voltage samples over time to a Python program, which then processes the data via downsampling, multiplication by the conjugate, and conversion to a decibel scale. The program finds the maximum power level measured over the interval and compared to a strength threshold. Whether the threshold has been met is displayed via LEDs on the tool. This tool will be used to decrease the resource intensivity of installing Z-Wave devices, leading to increased installer efficiency and lower call-center workload.\",\"PeriodicalId\":265421,\"journal\":{\"name\":\"2019 Systems and Information Engineering Design Symposium (SIEDS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Systems and Information Engineering Design Symposium (SIEDS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIEDS.2019.8735588\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Systems and Information Engineering Design Symposium (SIEDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIEDS.2019.8735588","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of a Portable Z-Wave Signal Detector for Home Security Installations
Many home automation systems use the wireless protocol Z-Wave for communication between devices in the network. Installers of such systems often face issues related to Z-Wave connectivity during installations, as devices must be placed so that Z-Wave signal strength between them is strong enough to add the device to the mesh network. The goal of this project is to design and prototype a device that measures Z-Wave signal strength to aid installers in the process of placing devices and troubleshooting device connectivity. While devices that measure Z-Wave signal strength currently exist, they are not optimized for installer use. Some devices require a proprietary license to operate, and some such as spectrum analyzers are expensive and have a large learning curve. The design's hardware consists of an antenna, software-defined radio (SDR), Raspberry Pi, LED array, activation button, battery, and housing. The antenna captures a modulated signal in the Z-Wave band and converts it to a voltage signal to be processed by the SDR. The voltage signal goes through an analog to digital converter in the SDR and is streamed into the Raspberry Pi as discrete voltage samples over time. The Raspberry Pi utilizes firmware called LibAirspy to interface to the SDR and forwards the voltage samples over time to a Python program, which then processes the data via downsampling, multiplication by the conjugate, and conversion to a decibel scale. The program finds the maximum power level measured over the interval and compared to a strength threshold. Whether the threshold has been met is displayed via LEDs on the tool. This tool will be used to decrease the resource intensivity of installing Z-Wave devices, leading to increased installer efficiency and lower call-center workload.