In this paper, a multiantenna wireless transmitter communicates with an information receiver while radiating RF energy to surrounding energy harvesters. The channel between the transceivers is known to the transmitter, but the channels between the transmitter and the energy harvesters are unknown to the transmitter. By designing its transmit covariance matrix, the transmitter fully charges the energy buffers of all energy harvesters in the shortest amount of time while maintaining the target information rate toward the receiver. At the beginning of each time slot, the transmitter determines the particular beam pattern to transmit with. Throughout the whole charging process, the transmitter does not estimate the energy harvesting channel vectors. Due to the high complexity of the system, we propose a novel deep Q-network algorithm to determine the optimal transmission strategy for complex systems. Simulation results show that deep Q-network is superior to the existing algorithms in terms of the time consumption to fulfill the wireless charging process.

Though the interest in learning IoT and AI involved in industry 4.0 is dramatically increasing in recent years, many universities have not integrated those up-to-date technologies and applications in engineering education. In this research, many aspects of IoT and AI applied in industry 4.0 are introduced in engineering curriculum development. The redesigned curriculum with innovative technology is developed for students to learn IoT, AI, machine learning, and smart sensors; and prepare engineering students in the demanding field of IoT, AI, and Industry 4.0 using new technologies, coupled with industry-based and problem-based hands-on learning. This work could have great impact on activating student interest and enthusiasm for learning engineering in comprehensive application and creativity.

With the Americans with Disabilities Act (ADA), the past two decades have seen a proliferation of Assistive Technology (AT) and its enabling impact on the lives of people with disabilities in the areas of accessing information, communication, and daily living activities. Due to recent emergence of the Internet of Things (IoT), the research of assistive robotics has been contributing to assisting humans to manipulate and communicate with the robot in complex unstructured environments. The ongoing revolution of Internet of Things (IoT), together with the growing diffusion of robots applied in everyday life and industry, makes Internet of Robotic Things (IoRT) as the future direction for assistive robotics research. New advanced technologies and services are explored in assisting humans. This study provides an overview of the IoT and applications into robotics based on the building blocks of the IoT, along with recent trends and issues relevant to accessing technology for people with disabilities. This research also discusses the technologies in IoT that would benefit the applications of assistive robotics. The most important research challenges to be faced are also highlighted.