Existing smart farming technology faces sustainability challenges due to high costs and environmental pollution. This study introduces a novel, sealed smart farming system utilizing misting technology to address these limitations. The system is designed to efficiently use water and nutrients, making it particularly suitable for high-value crop cultivation in urban environments with architectural constraints. Over a one-month experimental period, we monitored the system’s performance in a controlled environment. The methodology included setting up the system and regularly measuring water usage, nutrient delivery, and plant growth metrics. The experimental results showed a significant reduction in water usage compared to traditional methods, with precise control of micronutrient delivery. Additionally, the system’s ability to maintain a consistent sealed environment was demonstrated, which is crucial for optimal plant growth. The system’s portability and space utilization efficiency were also highlighted as major advantages. Furthermore, the system demonstrated potential for cultivation in extreme environments, such as water-scarce regions, by maintaining optimal indoor conditions for crop growth. Challenges such as nozzle clogging and uneven mist distribution were identified, indicating the need for further research in cartridge design and misting methods. Overall, this smart farming technology shows significant promise for enhancing global food security and contributing to sustainable agricultural development by minimizing water usage and optimizing nutrient management.

This study investigates the characteristics of a novel origami-based, elastomeric actuator and a soft gripper, which are controlled by hand gestures that are recognized through machine learning algorithms. The lightweight paper–elastomer structure employed in this research exhibits distinct actuation features in four key areas: (1) It requires approximately 20% less pressure for the same bending amplitude compared to pneumatic network actuators (Pneu-Net) of equivalent weight, and even less pressure compared to other actuators with non-linear bending behavior; (2) The control of the device is examined by validating the relationship between pressure and the bending angle, as well as the interaction force and pressure at a fixed bending angle; (3) A soft robotic gripper comprising three actuators is designed. Enveloping and pinch grasping experiments are conducted on various shapes, which demonstrate the gripper’s potential in handling a wide range of objects for numerous applications; and (4) A gesture recognition algorithm is developed to control the gripper using electromyogram (EMG) signals from the user’s muscles.

Robotic eye-gaze-based cueing has been studied and proved to be effective, in controlled environments, in achieving social functions as humans gaze. However, its dynamic adaptability in various real interactions has not been explored in-depth. This paper addresses a case where a simplistic robotic gaze fails to achieve effective social cueing in human–robot communication, primarily due to in-attentional blindness (IB), and presents a method that enables the robot to deliver gaze-based social signals adequately. To understand the implications of IB and figure out ways to overcome any limitations from IB, which frequently arise in task-oriented situations, we designed a set of 1-on-1 communication experiments consisting of a robotic tutor and human learners participating in multiple-choice quiz sessions (task-oriented situation). Here, multimedia contents were utilized alongside the robot as visual stimuli competing for the human’s attention. We hypothesized that quiz scores would increase when humans successfully recognize the robot’s gaze-based cue signals hinting answers. We compared the impacts of two different cueing methods: oblique cueing (OC), where cues were straightforwardly provided regardless of whether participants were potentially experiencing IB or not, and leading cueing (LC), where cueing procedures were led through achieving eye contact and securing the participants’ attention before signaling the cue. By comparing participants’ test scores achieved by the control group with no cueing (NC) and two experimental groups of OC and LC, respectively, we found that there was a significant increase in test scores only when the LC method was utilized. This experiment illustrates the importance of proactively guiding a user’s attention through sophisticated interaction design in effectively attaining a user’s attention and successfully delivering cues. In future studies, we aim to evaluate different methods by which a social robot can intentionally shift a human’s attention, such as incorporating stimuli from various multi-modal human communication channels.