Current positioning systems are primarily based on the Global Positioning System(GPS).Although the GPS is accurate within 10 m,it is mainly used for outdoor positioning services(Location-Based Service;LBS).However,sin...Current positioning systems are primarily based on the Global Positioning System(GPS).Although the GPS is accurate within 10 m,it is mainly used for outdoor positioning services(Location-Based Service;LBS).However,since satellite signals cannot penetrate buildings,indoor positioning has always been a blind spot for satellite signals.As indoor positioning applications are extensive with high commercial values,they have created a competitive niche in themarket.Existing indoor positioning technologies are unable to achieve less than 10 cmaccuracy except for the UltraWide Band(UWB)technology.On the other hand,the Bluetooth protocol achieves an accuracy of 1 to 2m.In this work,we use Bluetooth wireless signals to build a novel indoor positioning framework to avoid the high manufacturing costs involved in the UWB technology.The Bluetooth signals are combined with the results from artificial intelligence algorithms to improve accuracy.During laboratory indoor location tracking,the accuracy rate is 96%,which provides effective indoor tracking for the movement of people.展开更多
This work presents a fall detection system based on artificial intelligence.The system incorporates miniature wearable devices for fall detection.Fall detection is achieved by integrating a three-axis gyroscope and a ...This work presents a fall detection system based on artificial intelligence.The system incorporates miniature wearable devices for fall detection.Fall detection is achieved by integrating a three-axis gyroscope and a threeaxis accelerometer.The system gathers the differential data collected by the gyroscope and accelerometer,applies artificial intelligence algorithms for model training and constructs an effective model for fall detection.To provide easywearing and effective position detection,it is designed as a small device attached to the user’swaist.Experiment results have shown that the accuracy of the proposed fall detection model is up to 98%,demonstrating the effectiveness of the model in real-life fall detection.展开更多
文摘Current positioning systems are primarily based on the Global Positioning System(GPS).Although the GPS is accurate within 10 m,it is mainly used for outdoor positioning services(Location-Based Service;LBS).However,since satellite signals cannot penetrate buildings,indoor positioning has always been a blind spot for satellite signals.As indoor positioning applications are extensive with high commercial values,they have created a competitive niche in themarket.Existing indoor positioning technologies are unable to achieve less than 10 cmaccuracy except for the UltraWide Band(UWB)technology.On the other hand,the Bluetooth protocol achieves an accuracy of 1 to 2m.In this work,we use Bluetooth wireless signals to build a novel indoor positioning framework to avoid the high manufacturing costs involved in the UWB technology.The Bluetooth signals are combined with the results from artificial intelligence algorithms to improve accuracy.During laboratory indoor location tracking,the accuracy rate is 96%,which provides effective indoor tracking for the movement of people.
文摘This work presents a fall detection system based on artificial intelligence.The system incorporates miniature wearable devices for fall detection.Fall detection is achieved by integrating a three-axis gyroscope and a threeaxis accelerometer.The system gathers the differential data collected by the gyroscope and accelerometer,applies artificial intelligence algorithms for model training and constructs an effective model for fall detection.To provide easywearing and effective position detection,it is designed as a small device attached to the user’swaist.Experiment results have shown that the accuracy of the proposed fall detection model is up to 98%,demonstrating the effectiveness of the model in real-life fall detection.
