Quality of Life Prediction on Walking Scenes Using Deep Neural Networks and Performance Improvement Using Knowledge Distillation

• DOI: 10.3390/electronics12132907
• Publication Date: 2023-07-03T04:42:46Z
• Authors: Thanasit Rithanas...; Kitsaphon Thitisi...; Pittipol Kantavat; Boonserm Kijsirikul; Yuji Iwahori; Shinji Fukui; Kazuki Nakamura; Yoshitsugu Hayashi
• Keywords: Walkability

The well-being of residents is a top priority for megacities, which why urban design and sustainable development are crucial topics. Quality Life (QoL) used as an effective key performance index (KPI) to measure the efficiency city plan’s quantity quality factors. For dwellers, QoL pedestrians also significant. walkability concept evaluates analyzes in walking scene. However, traditional questionnaire survey approach costly, time-consuming, limited its evaluation area. To overcome these limitations, paper proposes using artificial intelligence (AI) technology evaluate data collected through virtual reality (VR) tools. proposed method involves knowledge extraction deep convolutional neural networks (DCNNs) information learning (DL) models infer scores. Knowledge distillation (KD) applied reduce model size improve real-time performance. experiment results demonstrate that practical can be considered alternative acquiring QoL.