Green House Smart Farming Echosystem

The future of farming has been one of the most talked-about issues on world forums, with the world population increasing yearly there is a special need to develop more efficient ways to grow food and distribute them effectively. This work discusses the design and implementation of a greenhouse smart farming echo system for the cultivation and distribution of plants using mushrooms as a focused product, linking a farm environment to a business market (cultivation processes and supply chain). A greenhouse farm smartly monitored with embedded devices, a control interface for these devices, and a web platform for product distribution and consumer management platform was developed to create a unified smart agricultural echo system. The embedded system has sensors that monitor the levels of light, temperature, soil moisture and humidity and automatically open the tap to water the farm. In addition, the supply chain was designed for the distribution of farm products. The prototype was fabricated and tested. The results showed that both the electronic part and the supply chain are working as proposed.

A Way of Bionic Control Based on EI, EMG, and FMG Signals

Creating highly functional prosthetic, orthotic, and rehabilitation devices is a socially relevant scientific and engineering task. Currently, certain constraints hamper the development of such devices. The primary constraint is the lack of an intuitive and reliable control interface working between the organism and the actuator. The critical point in developing these devices and systems is determining the type and parameters of movements based on control signals recorded on an extremity. In the study, we investigate the simultaneous acquisition of electric impedance (EI), electromyography (EMG), and force myography (FMG) signals during basic wrist movements: grasping, flexion/extension, and rotation. For investigation, a laboratory instrumentation and software test setup were made for registering signals and collecting data. The analysis of the acquired signals revealed that the EI signals in conjunction with the analysis of EMG and FMG signals could potentially be highly informative in anthropomorphic control systems. The study results confirm that the comprehensive real-time analysis of EI, EMG, and FMG signals potentially allows implementing the method of anthropomorphic and proportional control with an acceptable delay.

Eyes-Free Tongue Gesture and Tongue Joystick Control of a Five DOF Upper-Limb Exoskeleton for Severely Disabled Individuals

Spinal cord injury can leave the affected individual severely disabled with a low level of independence and quality of life. Assistive upper-limb exoskeletons are one of the solutions that can enable an individual with tetraplegia (paralysis in both arms and legs) to perform simple activities of daily living by mobilizing the arm. Providing an efficient user interface that can provide full continuous control of such a device—safely and intuitively—with multiple degrees of freedom (DOFs) still remains a challenge. In this study, a control interface for an assistive upper-limb exoskeleton with five DOFs based on an intraoral tongue-computer interface (ITCI) for individuals with tetraplegia was proposed. Furthermore, we evaluated eyes-free use of the ITCI for the first time and compared two tongue-operated control methods, one based on tongue gestures and the other based on dynamic virtual buttons and a joystick-like control. Ten able-bodied participants tongue controlled the exoskeleton for a drinking task with and without visual feedback on a screen in three experimental sessions. As a baseline, the participants performed the drinking task with a standard gamepad. The results showed that it was possible to control the exoskeleton with the tongue even without visual feedback and to perform the drinking task at 65.1% of the speed of the gamepad. In a clinical case study, an individual with tetraplegia further succeeded to fully control the exoskeleton and perform the drinking task only 5.6% slower than the able-bodied group. This study demonstrated the first single-modal control interface that can enable individuals with complete tetraplegia to fully and continuously control a five-DOF upper limb exoskeleton and perform a drinking task after only 2 h of training. The interface was used both with and without visual feedback.

The systematic evaluation of an embodied control interface for virtual reality

Embodied interfaces are promising for virtual reality (VR) because they can improve immersion and reduce simulator sickness compared to more traditional handheld interfaces (e.g., gamepads). We present a novel embodied interface called the Limbic Chair. The chair is composed of two separate shells that allow the user’s legs to move independently while sitting. We demonstrate the suitability of the Limbic Chair in two VR scenarios: city navigation and flight simulation. We compare the Limbic Chair to a gamepad using performance measures (i.e., time and accuracy), head movements, body sway, and standard questionnaires for measuring presence, usability, workload, and simulator sickness. In the city navigation scenario, the gamepad was associated with better presence, usability, and workload scores. In the flight simulation scenario, the chair was associated with less body sway (i.e., less simulator sickness) and fewer head movements but also slower performance and higher workload. In all other comparisons, the Limbic Chair and gamepad were similar, showing the promise of the Chair for replacing some control functions traditionally executed using handheld devices.

Data acquisition and slow control interface for the Mu2e experiment

The Mu2e experiment at the Fermilab Muon Campus will search for the coherent neutrinoless conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement by a factor of 10000 over existing limits. The Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates both the artdaq DAQ and the art analysis frameworks for event transfer, filtering, and processing. otsdaq is an online DAQ software suite with a focus on flexibility and scalability and provides a multi-user, web-based, interface accessible through a web browser. The data stream from the detector subsystems is read by a software filter algorithm that selects events which are combined with the data flux coming from a cosmic ray veto system. The Detector Control System (DCS) has been developed using the Experimental Physics and Industrial Control System (EPICS) open source platform for monitoring, controlling, alarming, and archiving. The DCS system has been integrated into otsdaq. A prototype of the TDAQ and the DCS systems has been built at Fermilab’s Feynman Computing Center. In this paper, we report on the progress of the integration of this prototype in the online otsdaq software.

Approaches for Motion Control Interface and Tele-Operated Overhead Crane Handling Tasks

This study aimed to identify the effects of different approaches to a motion control interface (MCI) in tele-operated crane handling tasks. In this study, due to the difficulty of applying the actual equipment to the experiment, we presented a prototype system of a tele-operated overhead handling (TOH) crane. Specifically, we investigated participants’ task performance including the accuracy of task completion during unloading, heart rate variation, workload, and the relationships between these factors when four motion control approaches were used: pointing (P), keyboard (K), orientation (O), hand-free gesture (HG). Experiments were conducted with two groups of participants: 21 university students and 11 crane operators used each of the four control methods. A task condition for handling iron blocks was tested. The efficacy of each motion control approach for task performance was evaluated by a within-subject experiment with a novice group. The expert group was used for comparing the task performance and satisfaction in the prototype system with the novices, evaluating whether the prototype system was reproducible for a real setting in the construction site. The results showed that the task completion time, the weight of physical demand, and the overall scores for workload were significantly impacted by the type of motion control: when HG was used, the task completion time increased. Particularly, using HG had the potential to increase the overall workload score, while physical laboriousness was also potentially increased by HG. Conversely, unloading accuracy, heart rate, and mental demand were not affected by motion control approaches. Generally, the expert group spent more time completing the tasks, but they performed better unloading accuracy than the novices in all methods. Ninety-one percent of the experts gave positive feedback on the reproducibility of the prototype system.

Development of Surface EMG Game Control Interface for Persons with Upper Limb Functional Impairments

In recent years, surface Electromyography (sEMG) signals have been effectively applied in various fields such as control interfaces, prosthetics, and rehabilitation. We propose a neck rotation estimation from EMG and apply the signal estimate as a game control interface that can be used by people with disabilities or patients with functional impairment of the upper limb. This paper utilizes an equation estimation and a machine learning model to translate the signals into corresponding neck rotations. For testing, we designed two custom-made game scenes, a dynamic 1D object interception and a 2D maze scenery, in Unity 3D to be controlled by sEMG signal in real-time. Twenty-two (22) test subjects (mean age 27.95, std 13.24) participated in the experiment to verify the usability of the interface. From object interception, subjects reported stable control inferred from intercepted objects more than 73% accurately. In a 2D maze, a comparison of male and female subjects reported a completion time of 98.84 s. ± 50.2 and 112.75 s. ± 44.2, respectively, without a significant difference in the mean of the one-way ANOVA (p = 0.519). The results confirmed the usefulness of neck sEMG of sternocleidomastoid (SCM) as a control interface with little or no calibration required. Control models using equations indicate intuitive direction and speed control, while machine learning schemes offer a more stable directional control. Control interfaces can be applied in several areas that involve neck activities, e.g., robot control and rehabilitation, as well as game interfaces, to enable entertainment for people with disabilities.