The goal of this course is to use the currently popular social media and government open IoT sensing data combined with a voice module (B3) to enable students to learn innovative IoT sensing and applications, including voice-controlled social media interfaces and appliances Module (B1), and use the artificial intelligence module (B4) recursive network for voice dialogue training, so that the media robot can automatically respond to voice inquiry, and can query the empty state near or at home. At the same time, start the home appliances to make demand actions, such as strong air purifier air purifier. The course is conducted in stages. The first stage is to learn the voice recognition module, and the second stage is to learn the home appliance control module. The first and second stages end to arrange an experiment for students to test the switch to control the appliance with voice. The third stage is Learning artificial intelligence modules, learning basic networks and advanced networks such as long and short memory networks, is expected to be used for dialogue robot training. This phase combines speech recognition and LineBot response for dialogue training, and arranges an experiment. The fourth phase is Combining geographic map resources and voice-driven LineBot air pollution distribution display and home decoration sensing linkage, a so-called social Internet of Things is formed. According to the schedule of this course, it is expected that three experimental results can participate in the results presentation meeting and the results compilation. The textbooks in this course can also expand the Alliance's community IoT module for use by foreign schools.

The goal of this course is to use the currently popular social media and government open IoT sensing data combined with a voice module (B3) to enable students to learn innovative IoT sensing and applications, including voice-controlled social media interfaces and appliances Module (B1), and use the artistic intelligence module (B4) recursive network for voice dialog training, so that the media robot can automatically respond to voice inquiry, and can query the empty state near or at home. At the same time, start the home appliances to make demand actions, such as strong air purifier air purifier. The course is conducted in stages. The first stage is to learn the voice recognition module, and the second stage is to learn the home appliance control module. The first and second stages end to arrange an experiment for students to test the switch to control the appliance with voice. The third stage is Learning artistic intelligence modules, learning basic networks and advanced networks such as long and short memory networks, is expected to be used for dialog robot training. This phase combines speech recognition and LineBot response for dialog training, and arranges an experiment. The fourth phase is Combining geographic map resources and voice-driven LineBot air pollution distribution display and home decoration sensing linkage, a so-called social Internet of Things is formed. According to the schedule of this course, it is expected that three experimental results can participate in the results presentation meeting and the results compilation. The textbooks in this course can also expand the Alliance's community IoT module for use by foreign schools.

1. Maneesh Rao, Internet of Things with Raspberry Pi 3, Apr. 2018.
2. 本計畫課程模組B-1，家電與能源管理應用開發模組教材
3. 本計畫課程模組B-4 ，深度學習時空間資料探勘教材
4. 本計畫課程模組B-3，家電與能源管理應用開發模組教材
5. 其他參考論文或網路上資料之自編教材

1. Maneesh Rao, Internet of Things with Raspberry Pi 3, Apr. 2018.
2. This plan course module B-1, home appliance and energy management application development module textbook
3. This planning course module B-4, in-depth learning of time and space data exploration textbook
4. This plan course module B-3, home appliance and energy management application development module textbook
5. Self-edited textbooks for other reference papers or online data