Different scent delivery methods may influence how scents are perceived in interactive systems. This study presents PlayScent, a custom-built research prototype comprising our in-house multi-module driver (UniODriver) and an integrated 3D-printed apparatus. Using a single-outlet design, PlayScent enables controlled comparison of atomizer, air pump, heater, and fan-based delivery methods under shared spatial conditions. Through a mixed-methods study, we develop a preliminary perceptual mapping and an initial perception vocabulary for scent delivery methods, relating user descriptions to measured physical parameters and identifying distinct perceptual tendencies across methods. Exploratory expert feedback further reflects on the possible relevance of these findings for design practice. Building on the empirical results, we outline illustrative design scenarios for future exploration. Together, this work offers an early design-oriented account of how delivery methods may be considered alongside scent selection in olfactory interaction design.

We present a breath-driven odor display device that enables spatial odor perception in virtual reality, relying on users’ natural inhalation rather than pumps or fans. The device supports rapid concentration adjustment through two models: a continuous gradient (monotonic concentration change with position) and a plume (intermittent, fluctuating patterns resembling natural dispersal). To explore its potential, we conducted a proof-of-concept evaluation across four tasks: concentration discrimination, direction and distance localization, and integrated position searching. Results show that the device can dynamically modulate odor concentration for spatial olfactory perception. Our findings further reveal complementary strengths and limitations of the two models—gradients support stable, precise cues, whereas plumes better emulate natural variability. This work introduces a simple yet effective method for simulating spatial odor experiences in VR, offering a lightweight, energy-efficient pathway that expands the design space for olfactory interaction research in virtual environments.

Olfactory interfaces are pivotal in HCI, yet their development is hindered by limited application scenarios, stifling the discovery of new research opportunities. This challenge primarily stems from existing design tools focusing predominantly on odor display devices and the creation of standalone olfactory experiences, rather than enabling rapid adaptation to various contexts and tasks. Addressing this, we introduce Mul-O, a novel task-oriented development platform crafted to aid semi-professionals in navigating the diverse requirements of potential application scenarios and effectively prototyping ideas. Mul-O facilitates the swift association and integration of olfactory experiences into functional designs, system integrations, and concept validations. Comprising a web UI for task-oriented development, an API server for seamless third-party integration, and wireless olfactory display hardware, Mul-O significantly enhances the ideation and prototyping process in multisensory tasks. This was verified by a 15-day workshop attended by 30 participants. The workshop produced seven innovative projects, underscoring Mul-O’s efficacy in fostering olfactory innovation.

Numerous studies have shown that integrating scents into movies enhances viewer engagement and immersion. However, creating such olfactory experiences often requires professional perfumers to match scents, limiting their widespread use. To address this, we propose OdorAgent which combines a LLM with a text-image model to automate video-odor matching. The generation framework is in four dimensions: subject matter, emotion, space, and time. We applied it to a specific movie and conducted user studies to evaluate and compare the effectiveness of different system elements. The results indicate that OdorAgent possesses significant scene adaptability and enables inexperienced individuals to design odor experiences for video and images.

As a prototype of the underwater Internet of Things-enabled maritime transportation systems, multi-Autonomous Underwater Vehicle (AUV)-based Underwater Wireless Networks (UWNs) have become an important research topic due to their distribution and robustness. In this paper, the concept of multi-AUV-based UWNs is first defined, where AUV is regarded as a network node, and communication among the AUVs is the potential network links. Then, to improve network scalability and controllability, a paradigm of Software Defined multi-AUV-based UWNs (SD-UWNs) is proposed, where the Software Defined Network (SDN) technique is used to upgrade the UWN architecture by directing intelligent network functions. Topology and artificial potential field theories are applied to construct a network control model for the SD-UWNs. Based on the efficient data sharing ability of the SD-UWNs, an early warning obstacle avoidance-enabled path planning scheme is proposed to guarantee safe sailing of the SD-UWNs, where comprehensive obstacle avoidance scenarios are taken into account. Simulation results demonstrate that the proposed method is effective in planning the cooperative operation for the SD-UWNs and is capable of performing accurate and reliable obstacle avoidance tasks.

Constructing olfactory interfaces on demand requires significant design proficiency and engineering effort. The absence of powerful and convenient tools that reduced innovation complexity posed obstacles for future research in the area. To address this problem, we proposed O&O, a modular olfactory interface DIY toolkit. The toolkit consists of: (1) a scent generation kit, a set of electronics and accessories that supported three common scent vaporization techniques; (2) a module construction kit, a set of primitive cardboard modules for assembling permutable functional structures; (3) a design manual, a step-by-step design thinking framework that directs the decision-making and prototyping process. We organized a formal workshop with 19 participants and four solo DIY trials to evaluate the capability of the toolkit, the overall user engagement, the creations in both sessions, and the iterative suggestions. Finally, design implications and future opportunities were discussed for further research.

Recently, researchers have become increasingly interested in finding new input methods for olfactory interfaces. Physical odor capture is a potential solution to this issue and, in order to make it more accessible for users, we designed a portable and fast smell capture prototype based on headspace technology and inspired by point-and-shoot cameras. We conducted a two-week diary study with 13 participants, in which they were allowed to freely use the prototype for odor capture activities. Through diary and interview feedback, we summarized factors such as the motivations of capturing, the collected odor types, and perceptual effects of odor replay. We found that the capture activities can positively affect user emotions, memory, or perception. User preferences on device parameters were also gathered to guide further design iterations. Physical odor capture has many potential applications in daily-life and other implications resulting from the study have been proposed for further research.

We present IRelics, a tangible interaction platform for the popularization of field archeology. IRelics allows users to experience archaeological field work activities as a serious game by using a set of tangible tools. We developed an innovative LWIR (Long Wavelength Infrared Rays) sensing system, which implements the design of tangible tools that provide real manipulation experiences. By interacting with IRelics, a player may experience different archaeological activities such as excavation and cleaning. We conducted two observations to evaluate the usability and effectiveness at archeology popularizing. Findings suggest that the IRelics platform can enhance the engagement of the participants by providing a positive and interactive environment while teaching them unfamiliar knowledge.