Vibration energy harvesting is a promising solution for powering battery-free IoT systems; however, the instability of ambient vibrations presents significant challenges, such as limited harvested energy, intermittent power supply, and poor adaptability to various applications. To address these challenges, this paper proposes ViPSN2.0, a modular and reconfigurable IoT platform that supports multiple vibration energy harvesters (piezoelectric, electromagnetic, and triboelectric) and accommodates sensing tasks with varying application requirements through standardized hot-swappable interfaces. ViPSN 2.0 incorporates an energyindication power management framework tailored to various application demands, including light-duty discrete sampling, heavyduty high-power sensing, and complex-duty streaming tasks, thereby effectively managing fluctuating energy availability. The platform’s versatility and robustness are validated through three representative applications: ViPSN-Beacon, using an ultra-lowcost structural PZT (ϕ35 mm, <0.002 $) to enable a BLE advertisement from a single transient fingertip press with 100 m line of sight; ViPSN-LoRa, supporting wireless communication powered by wave vibrations in actual marine environments (Bohai Bay) with per-uplink task energy compatible with kilometer-scale field links; and ViPSN-Cam, enabling intermittent image capture and wireless transfer, delivering one frame approximately every 15 s under typical conditions. Experimental results demonstrate that ViPSN 2.0 can reliably meet a wide range of requirements in practical battery-free IoT deployments under energy-constrained conditions.

Human-motion energy harvesting is emerging as a promising solution for wearable electronics and devices, offering a sustainable power source that extends operational longevity and enhances durability. However, current techniques and prototypes have yet to achieve fully interactive, battery-free functionality. This paper presents a battery-free interactive gaming system powered by energy harvested from transient fingertip motion. To ensure the reactivity, interactivity, and stability of the fingertip motion harvester (FMH), we employ a multistable structure. The FMH unit provides a reliable energy solution by utilizing precharged potential energy within dynamically varying potential wells. Additionally, the integration of a bistable screen design facilitates seamless gaming experiences, decouples game logic from user interface mechanics, and ensures rapid system recovery after power interruptions. Beyond advancing fundamental research, this work pioneers a practical battery-free interaction paradigm based on fingertip motion, with potential for broader battery-free user interfaces and low-power interactive systems.

Touch sensing is a prominent pillar technique in various human-computer interactive scenarios, especially when touchscreen-based capacitive touch sensing has become a representative in user-end electronics. An intelligent touch-sensing system captures the capacitive touch-sensing images to recognize the objects via machine learning techniques. However, collecting the training dataset is usually laborious and time-consuming, requiring specific coding skills and knowledge. In this article, we introduced vCapTouch, a data generation method to synthesize the touch sensing data, which can be directly employed to train a machine learning model and recognize the real touching behavior, significantly lowering the need for real dataset collection. The presented method is primarily based on the idea of the digital twin. We implemented the method with Unity3D, a game engine that enables high interactivity, is easy to use, and has a low cost. We evaluated the proposed method on eight users with different touch screen devices and proved the feasibility of synthesizing the touch sensing data.

The rise of the Internet of Things (IoT) has given birth to transformative and massively deployed computing applications that raise the significant issue of energy sources. It is impractical and irresponsible to rely on wires and batteries to power trillion-level devices. One promising prediction is that energy harvesting technologies will serve as alternative power sources for IoT devices. However, we might be losing this prophecy for lack of understanding of how novice developers comprehend energy in developing IoT. In response, we conducted a mentored physical prototyping study with a two-day workshop involving eight novice developers. The study consisted of qualitative and quantitative analyses, the artifacts, interviews with both novice developers and an expert, and implications of designs for future tools. The findings reveal informational gaps that demand educational efforts and assistive features to facilitate novice developers. We present major findings from the study and implications for the design of future tools.

In high-resolution and wide-swath synthetic aperture radar (SAR) systems, there are azimuth Doppler ambiguity and ghost ground moving targets (GMTs). Incorporated with an improved equivalent range model (IERM), this article explores a simultaneous scene imaging and GMT indication (GMTI) scheme with multiple beamforming for hypersonic vehicle-borne dive-trajectory high-squint multichannel SAR (HSV-DTHS-MC-SAR). First, the coarse-focusing imageries are recovered. Then, the CTV estimation with the dynamic-eigenspace-based adaptive sum and difference beams (EASDBs) is explored. After that, the SAR scene processing which enjoys “customized” beamforming, minimizes the ghost GMT and reconstructs the ambiguity-free scene image. Moreover, the proposed clutter suppression method generates the beamformer center in the desired GMT direction and reduces the beamformer sidelobe by using quadratic pattern constraints. Finally, the geometry and inverse projections are performed to calibrate the distortion arising from vertical velocity. Compared to the existing methods, the proposed scheme has innovations or improvements in CTV estimation, scene recovery, and cutter suppression. To be specific, it avoids the cumbersome CTV search and thus has lower computation, enjoys more concise and robust removal of ghost GMT in the scene, and frees the steering vector mismatch plus achieves a higher signal-to-clutter-and-noise ratio (SCNR). The extensive simulations confirm the effectiveness of our proposed scheme.

As a critical component for wireless communication, active phased array antennas face the restrictions of creating effective performance with the effect of randomness in the position of the array element, which are inevitably produced in the manufacturing and operating process of antenna. A new method for efficiently and effectively evaluating the statistic performance of antenna is presented, with consideration of randomness in element position. A coupled structural‐electromagnetic statistic model for array antenna is proposed from the viewpoint of electromechanical coupling. Lastly, a 12 × 12 planar array is illustrated to evaluate the performance of antenna with the saddle‐shaped distortion and random position error. The results show that the presented model can obtain the antenna performance quickly and effectively, providing an advantageous guidance for structural design and performance optimization for array antennas in wireless application.

The position error of array antenna significantly deteriorates the gain and sidelobe of the array, which seriously hinders the realization of high performance of communication antenna for Internet of Things (IoT). Based on the sensitivity analysis theory, the sensitivity of the array radiation field with respect to the position of the antenna element is derived. Besides, a novel design method of position tolerance for array antenna is proposed and applied to a 20 × 20 planar array. Compared with the array designed by traditional method, the gain loss is basically the same (being 0.5 dB), while the peak sidelobe level is lowered by 1.937 dB (φ = 0°)/1.586 dB (φ = 90°). Besides, the uncertainty analysis results show that the newly designed array has a much higher chance to achieve the desired performance, which fully demonstrates the innovation and effectiveness of the new method.