Development and Application of IoT Monitoring Systems for Typical Large Amusement Facilities.

The advent of internet of things (IoT) technology has ushered in a new dawn for the digital realm, offering innovative avenues for real-time surveillance and assessment of the operational conditions of intricate mechanical systems. Nowadays, mechanical system monitoring technologies are extensively utilized in various sectors, such as rotating and reciprocating machinery, expansive bridges, and intricate aircraft. Nevertheless, in comparison to standard mechanical frameworks, large amusement facilities, which constitute the primary manned electromechanical installations in amusement parks and scenic locales, showcase a myriad of structural designs and multiple failure patterns. The predominant method for fault diagnosis still relies on offline manual evaluations and intermittent testing of vital elements. This practice heavily depends on the inspectors' expertise and proficiency for effective detection. Moreover, periodic inspections cannot provide immediate feedback on the safety status of crucial components, they lack preemptive warnings for potential malfunctions, and fail to elevate safety measures during equipment operation. Hence, developing an equipment monitoring system grounded in IoT technology and sensor networks is paramount, especially considering the structural nuances and risk profiles of large amusement facilities. This study aims to develop customized operational status monitoring sensors and an IoT platform for large roller coasters, encompassing the design and fabrication of sensors and IoT platforms and data acquisition and processing. The ultimate objective is to enable timely warnings when monitoring signals deviate from normal ranges or violate relevant standards, thereby facilitating the prompt identification of potential safety hazards and equipment faults.

Intelligent wearable olfactory interface for latency-free mixed reality and fast olfactory enhancement.

Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay in odor manipulation, unwieldy dimensions, and limited number of odor supplies. Herein, we report a general strategy to solve these problems, which associates with a wearable, high-performance olfactory interface based on miniaturized odor generators (OGs) with advanced artificial intelligence (AI) algorithms. The OGs serve as the core technology of the intelligent olfactory interface, which exhibit milestone advances in millisecond-level response time, milliwatt-scale power consumption, and the miniaturized size. Empowered by robust AI algorithms, the olfactory interface shows its great potentials in latency-free mixed reality (MR) and fast olfaction enhancement, thereby establishing a bridge between electronics and users for broad applications ranging from entertainment, to education, to medical treatment, and to human machine interfaces.

Skin-Integrated Wireless Odor Message Delivery Electronics for the Deaf-blind.

Deaf-blindness limits daily human activities, especially interactive modes of audio and visual perception. Although the developed standards have been verified as alternative communication methods, they are uncommon to the nondisabled due to the complicated learning process and inefficiency in terms of communicating distance and throughput. Therefore, the development of communication techniques employing innate sensory abilities including olfaction related to the cerebral limbic system processing emotions, memories, and recognition has been suggested for reducing the training level and increasing communication efficiency. Here, a skin-integrated and wireless olfactory interface system exploiting arrays of miniaturized odor generators (OGs) based on melting/solidifying odorous wax to release smell is introduced for establishing an advanced communication system between deaf-blind and non-deaf-blind. By optimizing the structure design of the OGs, each OG device is as small as 0.24 cm3 (length × width × height of 11 mm × 10 mm × 2.2 mm), enabling integration of up to 8 OGs on the epidermis between nose and lip for direct and rapid olfactory drive with a weight of only 24.56 g. By generating single or mixed odors, different linked messages could be delivered to a user within a short period in a wireless and programmable way. By adopting the olfactory interface message delivery system, the recognition rates for the messages have been improved 1.5 times that of the touch-based method, while the response times were immensely decreased 4 times. Thus, the presented wearable olfactory interface system exhibits great potential as an alternative message delivery method for the deaf-blind.

Development of Multifunctional Detection Robot for Roller Coaster Track.

Recent advances in roller coasters accelerate the creation of complex tracks to provide stimulation and excitement for humans. As the main load-bearing component, tracks are prone to damage such as loose connecting bolts, paint peeling, corroded sleeper welds, corroded butt welds, reduced track wall thickness and surface cracks under complex environments and long-term alternating loads. However, inspection of the roller coaster tracks, especially the high-altitude rolling tracks, is a crucial problem that traditional manual detection methods have difficulty solving. In addition, traditional inspection is labor-intensive, time-consuming, and provides only discrete information. Here, a concept of the multifunctional detection robot with a mechanical structure, electrical control system, camera, electromagnetic ultrasonic probes and an array of eddy current probes for detecting large roller coaster tracks is reported. By optimizing the design layout, integrating multiple systems and completing machine testing, the multifunctional roller coaster track detection robot exhibits outstanding performance in track appearance, thickness and crack detection. This study provides great potential for intelligent detection in amusement equipment, railcar, train and so on.