Ziyao Zhou

Ziyao Zhou, Chen Shen, Tiancheng Cao et al.

Bluetooth Low Energy (BLE) is widely used in IoT systems because of its low power consumption, interoperability, and reliable bidirectional communication. However, its connection-oriented architecture introduces trade-offs among wake-up latency, throughput, and energy efficiency, limiting its suitability for burst-mode and on-demand sensing applications. Enhanced ShockBurst (ESB), a lightweight connectionless protocol supported by the same 2.4 GHz Nordic Semiconductor hardware, enables fast wake-up and efficient data transmission, but does not provide BLE-level robustness for sustained bidirectional communication. This work systematically benchmarks BLE and ESB on a unified Nordic nRF54L15 platform and proposes Enhanced-BLE, a hybrid framework that integrates the two protocols to extend conventional BLE operation. Experimental results show that ESB nearly halves packet transmission time and energy compared with BLE, doubles the achievable forward throughput, and reduces wake-up latency and energy by nearly twentyfold during intermittent operation. However, ESB reverse transmission may suffer packet loss, whereas BLE maintains reliable bidirectional communication. Enhanced-BLE addresses this trade-off through adaptive radio scheduling and coexistence-aware connection management, combining ESB-based high-throughput forward transmission with BLE-based reliable reverse communication. The framework enables BLE-to-ESB handover within approximately 18 ms and restores BLE operation within 49 ms from standby mode. Enhanced-BLE also achieves approximately twofold higher forward throughput than BLE while reducing wake-up latency. These results demonstrate a practical and hardware-compatible strategy for low-latency, high-throughput, energy-efficient, and reliable 2.4 GHz IoT communication.

Hen-Wei Huang, Claas Ehmke, Dawei Wang et al.

Ingestible electronic systems enable non-invasive, in situ sensing within the gastrointestinal (GI) tract, yet clinical translation has been limited by uncontrolled transit, short operational lifetimes, and unreliable wireless communication that prevent continuous monitoring. Here, we present a gastric-resident ingestible robotic platform that achieves week-long operation through integration of a bioinspired, electrically triggered release mechanism with a kirigami-enabled electronic architecture. A kirigami-patterned flexible printed circuit board spans the capsule body and deployable superelastic arms, enabling high-density integration of sensing, power management, and wireless modules within a constrained volume while tolerating large mechanical deformation during gastric residence. Stable retention and on-demand disassembly are achieved using thermally responsive polycaprolactone joints that transition from rigid to compliant states under electrical activation, avoiding dependence on variable chemical triggers. Reliable telemetry in the highly attenuating gastric environment is maintained using a dual-band Bluetooth Low Energy and sub-gigahertz module with RSSI- and throughput-aware adaptive transmission, balancing link robustness and energy consumption. We demonstrate long-term, continuous monitoring of gastric radiation exposure, enabling early detection of dose accumulation and providing a promising in vivo alternative to wearable or handheld dosimeters. Swine studies confirm stable gastric residence, sustained real-time telemetry, and safe gastrointestinal passage following triggered disassembly. This work establishes kirigami-enabled integration as a scalable strategy for long-term gastric-resident robotic systems.

Ziyao Zhou, Tiancheng Cao, Chen Shen et al.

Accurate time synchronization is essential for Internet of Things (IoT) systems, where multiple distributed nodes must share a common time base for coordinated sensing and data fusion. However, conventional synchronization approaches suffer from nondeterministic transmission latency, limited precision, or restricted bidirectional functionality. This paper presents a protocol-independent wireless timer synchronization method that exploits radio timeslots to transmit precisely timestamped beacons in a proprietary radio mode. By decoupling synchronization from upper-layer packet retransmissions and leveraging hardware-timed radio events, the proposed approach significantly reduces scheduling uncertainty and achieves nanosecond-level synchronization accuracy. Comprehensive experiments evaluate the impacts of synchronization frequency, RSSI, BLE connection interval, and throughput on synchronization performance. The results demonstrate that an optimal synchronization frequency of 1000 Hz yields an approximately 20 ns delay in the absence of communication stack activity while maintaining sub-500 ns accuracy under most realistic BLE traffic conditions. Furthermore, larger connection intervals, lower application throughput, and higher RSSI consistently improve synchronization quality by reducing radio resource contention and packet loss. The proposed scheme provides a general and high-precision synchronization solution suitable for resource-constrained IoT systems.

Ziyao Zhou, Chen Shen, Sicong Shen et al.

On demand sensing is emerging as a key paradigm in Internet of Things (IoT) systems, where devices remain in low power states and transmit data only upon event triggers. Such an operation requires wireless communication schemes that provide low latency, minimal wake up overhead, and high energy efficiency. However, widely adopted protocols such as Bluetooth Low Energy (BLE) rely on connection oriented mechanisms that incur non negligible latency and energy overhead during sleep wake transitions, limiting their effectiveness for event driven sensing. In this work, Nordic Semiconductor's proprietary Enhanced ShockBurst (ESB) protocol is investigated as an alternative communication scheme for low power on demand IoT systems. A systematic experimental comparison between ESB and BLE is presented on the same hardware platform, evaluating packet level latency, transmission energy, achievable throughput, wake up overhead under duty cycled operation, and bidirectional communication characteristics. Results show that ESB achieves a packet latency of 0.68 ms for a 244 byte payload, reduces per packet transmission time and energy by nearly 2x, increases maximum throughput by approximately 2x, and lowers wake up time and energy by up to 10x compared with BLE. To demonstrate system level impact, an implantable loop recorder prototype with FIFO triggered electrocardiogram transmission is implemented. The ESB based system enables rapid event driven communication with a minimum communication power of 0.5 mW and reduces total system power consumption by approximately 60 percent relative to BLE. These results highlight the limitations of connection oriented protocols for on demand sensing and establish ESB as a lightweight and effective communication alternative for energy constrained IoT applications, including biomedical implants and event driven monitoring systems.

Wo Long, Wenxin Zeng, Xiaoyu Zhang et al.

This research develops a sentiment-driven quantitative trading system that leverages a large language model, FinGPT, for sentiment analysis, and explores a novel method for signal integration using a reinforcement learning algorithm, Twin Delayed Deep Deterministic Policy Gradient (TD3). We compare the performance of strategies that integrate sentiment and technical signals using both a conventional rule-based approach and a reinforcement learning framework. The results suggest that sentiment signals generated by FinGPT offer value when combined with traditional technical indicators, and that reinforcement learning algorithm presents a promising approach for effectively integrating heterogeneous signals in dynamic trading environments.

Ziyao Zhou, Chen Chai, Weiru Yin et al.

The purpose of this paper is to develop a shared control takeover strategy for smooth and safety control transition from an automation driving system to the human driver and to approve its positive impacts on drivers' behavior and attitudes. A "human-in-the-loop" driving simulator experiment was conducted to evaluate the impact of the proposed shared control takeover strategy under different disengagement conditions. Results of thirty-two drivers showed shared control takeover strategy could improve safety performance at the aggregated level, especially at non-driving related disengagements. For more urgent disengagements caused by another vehicle's sudden brake, a shared control strategy enlarges individual differences. The primary reason is that some drivers had higher self-reported mental workloads in response to the shared control takeover strategy. Therefore, shared control between driver and automation can involve driver's training to avoid mental overload when developing takeover strategies.