Smart Trash Can Robot System with Integration of Internet of Things and Mobile Applications

Chang, Bao Rong; Tsai, Hsiu-Fen; Lyu, Jyong-Lin; Yin, Tang-Kai

doi:10.18494/sam.2019.2563

Cited by 8 publications

(7 citation statements)

References 19 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To reach the balance during the movement of the balance trolley, 17 based on Figure 17(a) and (b), the balance trolley can maintain balance and move forward stably while passing through the bumpy slopes. The technical background of iMonitor 18 includes IoT, mobile applications, databases, face recognition, face tracking, gas detection, and infrared thermal imaging.…”

Section: Experiments Results and Evaluationmentioning

confidence: 99%

Distributed sensing units deploying on group unmanned vehicles

Chang

Tsai

Lyu

et al. 2021

International Journal of Distributed Sensor Networks

Self Cite

View full text Add to dashboard Cite

This study aims to use two unmanned vehicles (aerial vehicles and ground vehicles) to implement multi-machine cooperation to complete the assigned tasks quickly. Unmanned aerial/ground vehicles can call each other to send instant inquiry messages using the proposed cooperative communication protocol to hand over the tasks between them and execute efficient three-dimensional collaborative operations in time. This study has demonstrated integrating unmanned aerial/ground vehicles into a group through the control platform (i.e. App operation interface) that uses the Internet of Things. Therefore, pilots can make decisions and communicate through App for cooperative coordination, allowing a group of unmanned aerial/ground vehicles to complete the tasks flexibly. In addition, the payload attached to unmanned air/ground vehicles can carry out multipurpose monitoring that implements face recognition, gas detection, thermal imaging, and video recording. During the experiment of unmanned aerial vehicle, unmanned aerial vehicle will plan the flight path and record the movement trajectory with global positioning system when it is on duty. As a result, the accuracy of the planned flight path achieved 86.89% on average.

show abstract

Section: Experiments Results and Evaluationmentioning

confidence: 99%

Distributed sensing units deploying on group unmanned vehicles

Chang

Tsai

Lyu

et al. 2021

International Journal of Distributed Sensor Networks

Self Cite

View full text Add to dashboard Cite

show abstract

“…(26) Figures 7(a) and 7(b) respectively show the actual operation of the self-balancing car moving on uphill and downhill sections while maintaining its balance and moving forward steadily. The technological background (27)(28)(29) for the iMonitor encompasses the following areas: IoT, mobile application, database system, AI facial recognition, face tracking, gas detection, and infrared thermography.…”

Section: Unmanned Mobile Multipurpose Monitoring Self-balancing Carmentioning

confidence: 99%

Unmanned Mobile Multipurpose Monitoring System—iMonitor

Chang¹,

Tsai²,

Lin³

et al. 2021

Sensors and Materials

Self Cite

View full text Add to dashboard Cite

Many available intelligent monitoring devices and applications only perform passive monitoring of the environment and notify the user when events occur, lacking the integration of viable technologies. In this work, we propose a multipurpose monitoring device that integrates cloud computing, the Internet of Things (IoT), and mobile applications to implement an unmanned mobile monitoring system for real-time monitoring and manipulation. The proposed system utilizes a self-balancing car as a stabilizing vehicle and a micro video camera that records images for AI facial tracking and recognition, combined with an infrared thermal imager to obtain forehead temperature. The recognized results are sent to a mobile device via a live video stream. The video stream can be recorded and images can be captured through a mobile application and uploaded to a cloud storage for playback and examination later. If the streamed video lacks sufficient illumination and cannot be viewed clearly, the system can be switched to infrared thermography to capture thermal images for monitoring the environment.The system can also be used as a mobile body temperature detector for the detection of abnormal body temperatures at a border control for quarantine inspections during the outbreak of contagious diseases. Furthermore, the system is equipped with four gas sensors to detect up to 12 different kinds of gaseous substances or particulate matter so that the user can be aware of the environmental quality around the self-balancing car. The outcome of this work can be applied to public health monitoring, dynamic crowd monitoring at airports and harbors, and the monitoring of hazardous or disaster-affected locations for search and rescue to reduce the costs associated with manual monitoring and the risk of exposure to hazards.This version has been created for advance publication by formatting the accepted manuscript. Some editorial changes may be made to this version.

show abstract

“…If the person has not registered before, it will display the word "Stranger" and his/her current forehead temperature. In the UGV, the camera sensor in iMonitor can accurately mark the person and display his/her ID with the forehead temperature when s/he is moving or standing, (22) as shown in Figs. 13(a) and 13(b).…”

Section: Face Recognition and Forehead Temperaturementioning

confidence: 99%

IoT-connected Group Deployment of Unmanned Vehicles with Sensing Units: iUAGV System

Chang¹,

Tsai²,

Lyu³

et al. 2021

Sensors and Materials

Self Cite

View full text Add to dashboard Cite

In recent years, the integration of air vehicles and ground vehicles has been a technological development with huge potential. However, making both types of vehicle work together concurrently is a major challenge. Therefore, we have developed a novel cooperative communication protocol to efficiently implement the collaborative operation between an unmanned aerial vehicle (UAV) and an unmanned ground vehicle (UGV). Through position sensing and time sensing, the UAV and UGV can achieve autonomous control by sending commands to each other. For example, the UGV can instantly pass a sensing-related task such as gas detection or obtaining a view of the ground from the air to the UAV, and the user can track the trajectory of the UAV flight through position sensing and time sensing to determine whether the UAV has done a task. Similarly, the UAV can send commands to the UGV to carry out sensing-related tasks such as face recognition and infrared thermal imaging of people on the ground. The UAV and UGV are not only equipped with a gas sensor and camera sensor, but they also have the built-in functions of position sensing and time sensing. According to experiments on the collaborative operation between UAVs and UGVs, the proposed approach enables the group deployment of unmanned vehicles to execute successfully three-dimensional collaborative operations that can be operated via an app without a ground control station. As a result, the proposed cooperative communication protocol through position sensing and time sensing efficiently realizes the IoT-connected group deployment of unmanned vehicles with sensing units.

show abstract

Smart Trash Can Robot System with Integration of Internet of Things and Mobile Applications

Cited by 8 publications

References 19 publications

Distributed sensing units deploying on group unmanned vehicles

Distributed sensing units deploying on group unmanned vehicles

Unmanned Mobile Multipurpose Monitoring System—iMonitor

IoT-connected Group Deployment of Unmanned Vehicles with Sensing Units: iUAGV System

Contact Info

Product

Resources

About