基于WiFi指纹定位技术的智能考勤系统的设计与实现
|
摘要
文中针对智能教室中考勤问题,提出了一种基于WiFi指纹定位技术的考勤系统,在定位中提出了一种基于缩放权重的KNN算法(Scale Weight KNN,SW-KNN),通过实验得出SW-KNN算法比经典的K最近邻法算法定位精度提高,通过该算法的指纹定位能够实现对学生的非觉察式考勤,提高教师的工作效率,节约人力物力,提高了教学活动的智能化。
In this paper,an attendance system based on WiFi fingerprint location technology is proposed for the problem of attendance in the intelligent classroom. A KNN algorithm(Scale Weight KNN,SWKNN)based on the scaling weight is proposed in the location. The experimental results show that the SW-KNN algorithm is more accurate than the classic K nearest neighbor algorithm,and through the algorithm,the location accuracy is improved. It can realize students' unaware attendance by the method of location,and it can improve teachers' work efficiency,save manpower and material resources,and improve the intelligence of teaching activities.
In this paper,an attendance system based on WiFi fingerprint location technology is proposed for the problem of attendance in the intelligent classroom. A KNN algorithm(Scale Weight KNN,SWKNN)based on the scaling weight is proposed in the location. The experimental results show that the SW-KNN algorithm is more accurate than the classic K nearest neighbor algorithm,and through the algorithm,the location accuracy is improved. It can realize students' unaware attendance by the method of location,and it can improve teachers' work efficiency,save manpower and material resources,and improve the intelligence of teaching activities.
引文
[1]陆音,缪辉辉.复杂室内环境下的WiFi定位技术研究[J].计算机科学,2016,43(11):152-154.
[2]钱志鸿,孙大洋,LEUNG Victor.无线网络定位综述[J].计算机学报,2016,39(6):1237-1256.
[3]肖亚龙,张士庚,王建新.一种基于对维标度和区域细化的无线室内定位方法[J].计算机学报,2017,40(8):1918-1931.
[4]黄旭,范婧,吴茂念,等.基于WiFi指纹定位技术的智能停车场系统的设计与实现[J].计算机科学,2016,43(6):512-515.
[5]唐洋,白勇,马跃,等.基于WiFi的指纹匹配算法在室内定位中的应用研究[J].计算机科学,2017,43(4):73-75.
[6]李新春,候跃.基于改进AP选择和K最近邻法算法的室内定位技术[J].计算机应用,2017,37(11):3276-3280,3287.
[7]辛英.基于k-邻近算法的手写识别系统的研究与实现[J].电子设计工程,2018,26(7):27-30.
[8]王玙璠,艾浩军,涂卫平.Wi-Fi指纹聚类在室内感兴趣区域定位中的应用[J].计算机应用,2016,36(2):488-491.
[9] Chengwen Luo,Long Cheng,Mun Choon Chan.Pallas:self-bootstrapping fine-grained passiveindoor localization using WiFi monitors[J].IEEETransactions on Mobile Computing,2017,16(2):466-481.
[10]Dong Li,Baoxian Zhang,Cheng Li,et al.A feature-scaling-based k-nearest neighbor algorithm forindoor positioning systems[J].IEEE Internet ofThings Journal,2016,3(4):590-597.
[11]Yuanchao Shu,Member,IEEE,Yinghua Huang.Gradient-Based Fingerprinting for Indoor Localization and Tracking[J].IEEE Transactions on Elec-tronics,2016,63(4):2424-2433.
[12]韦春玲,王步飞.基于WLAN接收信号强度特征的室内活动识别[J].计算机应用,2017,37(5):1326-1330.
[13]霍欢,杨沪沪,郑德原,等.一种改进的RSSI指纹库定位算法[J].计算机应用研究,2017,34(9):2786-2790.
[14]Devijver P.A,Kittler J.Pattern recognition:a statistical approach[J].Image and Vision Computing,1985,3(2):87-88.
[15]陈淑敏,乔晓田,毛佳,等.基于接收信号强度(RSSI)的室内二次定位方法[J].传感技术学报,2015,28(4):572-577.
[16]武一,张冀钊.基于Android平台改进的室内WiFi定位算法的研究[J].电子技术应用,2017,43(3):77-79.
[2]钱志鸿,孙大洋,LEUNG Victor.无线网络定位综述[J].计算机学报,2016,39(6):1237-1256.
[3]肖亚龙,张士庚,王建新.一种基于对维标度和区域细化的无线室内定位方法[J].计算机学报,2017,40(8):1918-1931.
[4]黄旭,范婧,吴茂念,等.基于WiFi指纹定位技术的智能停车场系统的设计与实现[J].计算机科学,2016,43(6):512-515.
[5]唐洋,白勇,马跃,等.基于WiFi的指纹匹配算法在室内定位中的应用研究[J].计算机科学,2017,43(4):73-75.
[6]李新春,候跃.基于改进AP选择和K最近邻法算法的室内定位技术[J].计算机应用,2017,37(11):3276-3280,3287.
[7]辛英.基于k-邻近算法的手写识别系统的研究与实现[J].电子设计工程,2018,26(7):27-30.
[8]王玙璠,艾浩军,涂卫平.Wi-Fi指纹聚类在室内感兴趣区域定位中的应用[J].计算机应用,2016,36(2):488-491.
[9] Chengwen Luo,Long Cheng,Mun Choon Chan.Pallas:self-bootstrapping fine-grained passiveindoor localization using WiFi monitors[J].IEEETransactions on Mobile Computing,2017,16(2):466-481.
[10]Dong Li,Baoxian Zhang,Cheng Li,et al.A feature-scaling-based k-nearest neighbor algorithm forindoor positioning systems[J].IEEE Internet ofThings Journal,2016,3(4):590-597.
[11]Yuanchao Shu,Member,IEEE,Yinghua Huang.Gradient-Based Fingerprinting for Indoor Localization and Tracking[J].IEEE Transactions on Elec-tronics,2016,63(4):2424-2433.
[12]韦春玲,王步飞.基于WLAN接收信号强度特征的室内活动识别[J].计算机应用,2017,37(5):1326-1330.
[13]霍欢,杨沪沪,郑德原,等.一种改进的RSSI指纹库定位算法[J].计算机应用研究,2017,34(9):2786-2790.
[14]Devijver P.A,Kittler J.Pattern recognition:a statistical approach[J].Image and Vision Computing,1985,3(2):87-88.
[15]陈淑敏,乔晓田,毛佳,等.基于接收信号强度(RSSI)的室内二次定位方法[J].传感技术学报,2015,28(4):572-577.
[16]武一,张冀钊.基于Android平台改进的室内WiFi定位算法的研究[J].电子技术应用,2017,43(3):77-79.