In recent years, fruit theft has become a serious social problem in Japan, where conventional surveillance measures are limited due to the unique challenges in agricultural areas, such as limited power supply and large areas. To address this, previous studies have developed battery-powered, microphone-based theft detection systems that operate on microcontrollers; however, achieving high classification accuracy under severe resource constraints remains a challenge. This paper presents a design and training methodology for a compact, high-accuracy sound classification model for fruit theft prevention. Our approach combines Depthwise Separable Convolution (DSC) for efficient feature extraction with Ensemble Distillation (EnD), which transfers knowledge from two teacher models with distinct feature extraction approaches. Experiments on a three-class task (environmental sounds, speech, and footsteps) demonstrated that the proposed model achieved an F1-score of 88.61%, an improvement of 12.00 percentage points over the baseline. The inference memory usage was limited to 49 kB, and including the entire system for processes other than deep learning inference, the total memory usage remained within 160 kB, well below the 256 kB RAM capacity of the target hardware. Moreover, the model achieved an inference time of approximately 0.4519 seconds per 1-second audio segment on a Seeeduino XIAO nRF52840 micro-controller. These results confirm the practical feasibility of the proposed system as a robust AI-based surveillance solution under strict resource constraints for real-world orchard applications.

There is frozen shoulder that a patient feels pain around the shoulder if the shoulder is moved in everyday life. It is necessary for the patient with the frozen shoulder to receive the rehabilitation for improvement of the QOL in the hospital, and it is important that the load of the physical therapist is reduced. To solve them, various machines and robots of the rehabilitation for the frozen shoulder are studied and developed. It is not suitable to repeat predefined motions to trace the general rehabilitation motion, since the motion of the shoulder in the rehabilitation should be adapted to the condition of each patient. Therefore, we are developing the rehabilitation robot for the frozen shoulder based on the direct teaching and playback motion. This paper describes the development of apparatus adapting each motion in the rehabilitation in the hospital normally. First, the motions in the rehabilitation are analyzed, the mechanism of the apparatus is considered based on the analysis. After that, the apparatus with five actuators is developed practically, and the direct teaching and playback motion are investigated by the participant that wears the apparatus. As a result, the realization of the apparatus is verified.

In Japanese fruit-growing regions, fruit theft is a significant issue. Traditional anti-theft methods are fraught with various shortcomings and are often ineffective. To address this, we have developed a new approach for preventing fruit theft: a device that detects suspicious sounds by integrating a sound sensor with a compact, low-power microcontroller. This paper presents a suspicious sound detection system designed for a fruit theft alert device. It details the development of a deep learning model for detecting suspicious sounds, covering aspects from data collection to model training and evaluation. Despite operating on a microcontroller with limited memory and computational power, the system under development has achieved a classification accuracy of up to 78.5% in F1-score for footsteps, speech, and other environmental sounds.

The measurement of walking is important for evaluating the health of elderly people. This evaluation is performed by experts in gait assessment (such as doctors or physiotherapists), who vary in terms of skill. To guarantee evaluative quality, engineering of gait-measurement solutions is desired. This paper describes a method of quantifying tacit physiotherapist knowledge of walk rehabilitation by tracking and analysing their eyes. We constructed the eye-tracking system to extract the points of gaze of multiple physiotherapists. The result shows that proficient physiotherapists exhibit special eye movements, which we defined as `rhythmical'. We evaluated the proficiencies of all subjects based on their rhythmical-eye movement. It is clear that proficiency does not increase linearly with rhythmical-eye movement, but instead exhibits a staircase-like behaviour. Consequently, we elucidated that the `rhythmical-eye movement' is one part of tacit knowledge of the proficient physiotherapists. And it is useful to establish the walking measurement closer to the proficient physiotherapists.

It is important to automate a heavy and hard task for workers. One of the hard tasks is that the worker picks up the bed sheet after washing, spreads it and enters it to ironing machine. In Japan, washing machine and ironing machine are working in the factory. However, the task such that the bed sheet is entered to ironing machine is not automated yet. We have developed handling machine to spread the bed sheet. However, there are some problems in successful rate and time cost. This paper describes the new handling machine to solve the problems. The new handling machine include the new algorithm and new robot arm is developed. And experiments are performed using real bed sheets. As a result, it is confirmed that the successful rate is increased, and time cost is decreased.

Increasing the export of fruit is vital for the Japanese economy. In this study, we focused on the peach trade as it is the third most transported fruit in Japan. The peach is a very sensitive fruit; therefore, proper packaging is important. We proposed a special packing sheet that we named the “concavo-convex sheet” developed through a simple mechanism. However, there were some problems in creating this sheet. This study describes the new mechanism for creating the concavo-convex sheet, and a real machine using the installed mechanism was developed. As a result, it was confirmed that the sheet can be realized by the new machine.

An important goal for the Japanese economy involves increasing the export of fruits. Especially, the export of peaches to Taiwan is an important part of trade for Japan. However, the peach fruit moth poses a serious problem. The moth is not native to Taiwan. Therefore, the moths that are exported with peaches may cause ecological damage in Taiwan. We are in the process of developing a peach fruit inspection system involving the use of X-rays. A handling unit that is a part of the inspection system is required to softly hold the peach without damaging it. This study describes a concavo-convex sheet developed by two nonwoven fabric clothes that is adapted for the inspection system. There are two important factors involved for incorporating the sheet in the inspection system, namely, the friction coefficient of the sheet and damage protection for the peaches. These factors are investigated by performing experiments that use several real, fresh peaches. The results confirm that the concavo-convex sheet satisfies the important properties necessary to employ the system for peach fruit inspection.

This paper describes an unique sheet developed from non-woven fabric that can be used to reduce transportation shock experienced by fruits that are easily damaged, such as peaches or strawberries, when transporting to foreign countries where there is a significant demand for these fruits. The proposed sheet comprises two non-woven fabric cloths suitable for packing these types of fruit. The non-woven cloth has useful characteristics such as air permeability, sealing properties, and X-ray transmission properties that make it suitable for transporting easily damaged fruit. In this paper, the application of the proposed sheet is applied for the packing of the fruits, however, the sheet that has the air permeability and shock resistance property is useful for the assistive robot and human interaction robot. And, the sheet is made manually, since the method to produce it is not constructed. The task of the human is reduced, if the mechanism for making the sheet can be realized. This paper describes that the properties of the sheet are introduced, and that the performance is investigated by experimental methods. Finally, the mechanism for producing the sheet is described and investigated using an experimental prototype.

Patients with Extension Lag cannot extend their knee straightly single-handedly. However, they can extend their knee without pain, if the other (a physical therapist (PT)) stretch the knee. The recovery of the Extension Lag is not necessary surgery, and is often enough only to perform rehabilitation. However, the rehabilitation of the Extension Lag is hard work for the PTs. This paper proposes the control algorithm for the automatic rehabilitation of the Extension Lag by adapting the Knee Assistive Instruments for Rehabilitation (KAI-R) that has been developed for the walking rehabilitation after the surgery of the Total Knee Arthroplasty (TKA) in order to reduce the load of the PT. The safety and the effectiveness of the robot are necessary to be verified, because we are going to adopt the robot to a clinical trial. First, the validity of the motion of the robot that is installed the control algorithm is confirmed by the high speed movie camera. Secondly, the effectiveness is investigated by using surface myoelectric potential. Thirdly, the motion of the robot is confirmed by the doctor and the PTs. It is clear that the robot for the rehabilitation of the Extension Lag can be adopted to a clinical trial.