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Due to the popularity of smart devices, traditional one-way teaching methods might not deeply attract school students’ attention, especially for the junior high school students, elementary school students, or even younger students, which is a critical issue for educators. Therefore, we develop an intelligent interactive education system, which leverages wearable devices (smart watches) to accurately capture hand gestures of school students and respond instantly to teachers so as to increase the interaction and attraction of school students in class. In addition, through multiple physical information of school students from the smart watch, it can find out the crux points of the learning process according to the deep data analysis. In this way, it can provide teachers to make instant adjustments and suggest school students to achieve multi-learning and innovative thinking. The system is mainly composed of three components: (1) smart interactive watch; (2) teacher-side smart application (App); and (3) cloud-based analysis system. Specifically, the smart interactive watch is responsible for detecting the physical information and interaction results of school students, and then giving feedback to the teachers. The teacher-side app will provide real-time learning suggestions to adjust the teaching pace to avoid learning disability. The cloud-based analysis system provides intelligent learning advices, academic performance prediction and anomaly learning detection. Through field trials, our system has been verified that can potentially enhance teaching and learning processes for both educators and school students.

For 5G wireless communications, the 3GPP Narrowband Internet of Things (NB-IoT) is one of the most promising technologies, which provides multiple types of resource unit (RU) with a special repetition mechanism to improve the scheduling flexibility and enhance the coverage and transmission reliability. Besides, NB-IoT supports different operation modes to reuse the spectrum of LTE and GSM, which can make use of bandwidth more efficiently. The IoT application grows rapidly; however, those massive IoT devices need to operate for a very long time. Thus, the energy consumption becomes a critical issue. Therefore, NB-IoT provides discontinuous reception operation to save devices' energy. But, how to further reduce the transmission energy while ensuring the required ultra-reliability is still an open issue. In this paper, we study how to guarantee the reliable communication and satisfy the quality of service (QoS) while minimizing the energy consumption for IoT devices. We first model the problem as an optimization problem and prove it to be NP-complete. Then, we propose an energy-efficient, ultra-reliable, and low-complexity scheme, which consists of two phases. The first phase tries to optimize the default transmit configurations of devices which incur the lowest energy consumption and satisfy the QoS requirement. The second phase leverages a weighting strategy to balance the emergency and inflexibility for determining the scheduling order to ensure the delay constraint while maintaining energy efficiency. Extensive simulation results show that our scheme can serve more devices with guaranteed QoS while saving their energy effectively.

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