Traded and combined cooperative control of a smart wheelchair

This article deals with a human–machine cooperative system for the control of a smart wheelchair for people with motor disabilities. The choice of a traded control mode is first argued. The paper then pursues two objectives. The first is to describe the design of the cooperative system by focusing on the dialogue and the interaction between the pilot and the robot. The second objective is to introduce a new cooperative mode. In this one, three features are proposed: two semi-autonomous features, a wall following and a doorway crossing, during which the user can intervene punctually to rectify a trajectory or a path, and an assisted mode where, conversely, the machine intervenes in a manual control to avoid obstacles. This mode of intervention of an entity, human or machine, supervising a movement controlled by the other is referred as “combined control.” Examples of scenarios exploiting the cooperative capabilities of the system are presented and discussed.

An Effective Combination of PLC and Microcontrollers for Centralized Traffic Control and Monitoring System

In this paper, a smart and centralized traffic light control and monitoring system is proposed to control the modern transportation systems and make the city safer, using programmable logic controllers (PLCs) and programmable electronic microcontrollers. A camera is used to monitor the mishaps during the traffic flow of vehicles. The system has four modes, i.e., auto-control mode (ACM), manual control mode (MCM), central control mode (CCM), and remote control mode (RCM). In the auto-control mode (ACM), the traffic light signals are controlled automatically through programmable electronic microcontrollers at specific times, while the manual control mode (MCM) controls the traffic light signals manually (on–off switches) according to the traffic congestion. The central control mode (CCM) is considered to be a centralized mode, where the programmable logic controller (PLC) is used by a computer workstation. In this mode, the traffic light signals are controlled by a ladder logic program of the PLC. The third mode, RCM, is linked with the second mode, CCM; in this mode, the traffic light signals are remotely controlled through the software by transferring programmable logic controller (PLC) functions to the software interface. As a result, this transportation system can also be controlled remotely. The designed system delivers suitable, flexible, and reliable control for traffic signaling and transportation.

Smart Incubator for Preterm Neonatal Using Kangaroo Mother Care

Kangaroo mother care is an apparatus that provides closed and controlled environmental for the preterm babies. A Preterm birth is commonly defined as any birth base 37 weeks completed weeks of gestation period. This paper deals with cost effective design of incubator that monitors parameters like pulse rate, temperature, humidity, child security and the readings will be continuously displayed In the LED screen and also monitoring the details to the corresponding doctor, nurse and parents by using GSM. The power failure problem is also eliminated by using solar panel. We also intimate the parents about feeding time, dressing time, ear check, eye check. But many of the existing system does not mentioned about above problem and have adopted only with humidity and temperature and also by manual control. So the main objective of this research is to overcome drawbacks and provide eco friendly service to all common people.

Sufficiency of the BOT-2 short form to screen motor competency in preschool children with strabismus

Background Strabismus is one of the most common visual disorders in children, with a reported prevalence of 2.48% in preschoolers. Additionally, up to 89.9% of preschool children with strabismus do not have normal stereopsis. Whether this lack of normal stereopsis affects the motor competency of preschool children with strabismus is unknown. The Bruininks-Oseretsky Test of Motor Proficiency Second Edition short form (BOT-2 SF) can be a useful tool for screening; however, its sufficiency as a diagnostic tool for children with various disorders is controversial. Objective The aims of this study were thus to examine motor competency in preschool children with strabismus by using the BOT-2 and to evaluate the usefulness of the BOT-2 SF to identify those at risk for motor competency issues. Methods Forty preschool children (aged 5–7 years) with strabismus were recruited, all of whom had abnormal stereopsis. The BOT-2 complete form (CF) was administered to all children. The BOT-2 CF was administered to all children. The scores of the BOT-2 SF were extracted from the relevant items of the BOT-2 CF for further analysis. Results The prevalence of children with strabismus who had below average performance in the composites of “Fine Manual Control”, “Manual Coordination”,”Body Coordination”, and “Strength and Agility” were 15%, 70%, 32.5%, and 5%, respectively, on the BOT-2 CF. Compared with these results, the sensitivity of the BOT-2 SF was 33.33% (95% CI = 7.49%–70.07%) and the specificity was 100% (95% CI = 88.78%–100%). Conclusion Preschool children with strabismus had a high prevalence of impaired motor competency, especially in fine motor competency. The BOT-2 SF was not as sensitive in identifying motor difficulties in preschool children with strabismus. Therefore, the BOT-2 CF is recommended for evaluating motor proficiency in preschool children with strabismus.

Improvement Realized Through Digitized Engineering Business Process

Engineering Division provides services & support to Operations and Projects. Division develops deliverable / report / recommendation for various studies, operation issues related to Engineering, root cause analysis, etc. Division receives an average of five request in a week. Division is handling 175+ studies at a time with support of multiple discipline Engineers within division and are in different stages. The division was handling the complete business process manually with dedicated resources to track the review, approval, execution and progress monitor. It was difficult to track all the steps since the information were scattered with many stakeholders and manual entries are not robust / fool proof. The manual control was insufficient to manage document movement, monitoring engineering activities and progress. This paper highlights the methodology used to digitalize the business process and also the improvement / benefit realized.

Artificial intelligence-controlled pole balancing using an Arduino board

Automation Process (AP) is an important issue in the current digitized world and, in general, represents an increase in the quality of productivity when compared with manual control. Balance is a natural human capacity as it relates to complex operations and intelligence. Balance Control presents an extra challenge in automation processes, due to the many variables that may be involved. This work presents a physical balancing pole where a Reinforcement Learning (RL) agent can explore the environment, sense its position through accelerometers, and wirelessly communicate and eventually learns by itself how to keep the pole balanced under noise disturbance. The agent uses RL principles to explore and learn new positions and corrections that lead toward more significant rewards in terms of pole equilibrium. By using a Q-matrix, the agent explores future conditions and acquires policy information that makes it possible to maintain stability. An Arduino microcontroller processes all training and testing. With the help of sensors, servo motors, wireless communications, and artificial intelligence, components merge into a system that consistently recovers equilibrium under random position changes. The obtained results prove that through RL, an agent can learn by itself to use generic sensors, actuators and solve balancing problems even under the limitations that a microcontroller presents.

Advanced Alarm Method Based on Driver’s State in Autonomous Vehicles

In autonomous driving vehicles, the driver can engage in non-driving-related tasks and does not have to pay attention to the driving conditions or engage in manual driving. If an unexpected situation arises that the autonomous vehicle cannot manage, then the vehicle should notify and help the driver to prepare themselves for retaking manual control of the vehicle. Several effective notification methods based on multimodal warning systems have been reported. In this paper, we propose an advanced method that employs alarms for specific conditions by analyzing the differences in the driver’s responses, based on their specific situation, to trigger visual and auditory alarms in autonomous vehicles. Using a driving simulation, we carried out human-in-the-loop experiments that included a total of 38 drivers and 2 scenarios (namely drowsiness and distraction scenarios), each of which included a control-switching stage for implementing an alarm during autonomous driving. Reaction time, gaze indicator, and questionnaire data were collected, and electroencephalography measurements were performed to verify the drowsiness. Based on the experimental results, the drivers exhibited a high alertness to the auditory alarms in both the drowsy and distracted conditions, and the change in the gaze indicator was higher in the distraction condition. The results of this study show that there was a distinct difference between the driver’s response to the alarms signaled in the drowsy and distracted conditions. Accordingly, we propose an advanced notification method and future goals for further investigation on vehicle alarms.

Optimization of Water Quantity with Smart Agriculture in IOT

In this paper, we propose fostering a framework ideally watering horticultural harvests dependent on a remote sensor organization. This work planned to plan and foster a control framework utilizing hub sensors in the harvest field with information the executives by means of cell phone and a web application. The three parts are equipment, web application, and portable application. The principal segment was planned and executed in charge box equipment associated with gather information on the harvests. Soil dampness sensors are utilized to screen the field, associating with the control box. The subsequent segment is an electronic application that was planned and executed to control the subtleties of yield information and field data. This segment applied information mining to break down the information for anticipating appropriate temperature, stickiness, and soil dampness for ideal future administration of harvests development. The last part is essentially used to control crop watering through a versatile application in a cell phone. This permits either programmed or manual control by the client. The programmed control utilizes information from soil dampness sensors for watering. Be that as it may, the client can pick manual control of watering the harvests in the useful control mode. The framework can send notices through LINE API for the LINE application. The framework was executed and tried in Makhamtia District, Suratthani Province, Thailand. The outcomes demonstrated the execution to be valuable in agribusiness. The dampness content of the dirt was kept up with properly for vegetable development, lessening costs and expanding rural usefulness. Also, this work addresses driving farming through computerized development.