IoT (Internet of Things) has attracted a lot of attention recently. IoT devices need to report their data or status to base stations at various frequencies. The IoT communications observed by a base station normally exhibit the following characteristics: (1) massively connected, (2) lightly loaded per packet, and (3) periodical or at least mostly predictable. The current design principals of communication networks, when applied to IoT scenarios, however, do not fit well to these requirements. When a large number of devices contend to send small packets, the signaling overhead is not cost-effective. To address this problem, our previous work [1] proposes the Hint protocol, which is slot-based and schedule- oriented for uploading IoT devices' data. In this work, we extend [1] to support data transmissions for multiple resource blocks. We assume that the uplink payloads from IoT devices are small, each taking very few slots (or resource blocks), but devices are massive. The main idea is to "encode" information in a tiny broadcast that allows each device to "decode" its transmission slots, thus significantly reducing transmission overheads and contention overheads. Our simulation results verify that the protocol can significantly increase channel utilization compared with traditional schemes.

E-healthcare games are a new patient care tool for providing fun, on-line monitoring enabled lifestyle, and a way for redefining traditional doctor-patient relationship. In this work, we demonstrate the use of intelligent sensors to capture patient behaviors for home healthcare. We design a new e-healthcare game user interface, iCube, for monitoring and recording patient activities. The iCube is a 3D game which has six display panels on the surfaces of a 3D cube embedded with a zigbee interface and some sensors for behavior monitoring. To prove its concept, we implement a Spot the Difference game. When a player is playing the game, the iCube can capture the player's hand shaking, rolling response, and visual capability. Those collected data are then sent to a database for spotting the progress/difference of the player over a long period time.