Autonomous surface vessel for search and rescue operation

Search and rescue operation is performed to save human life, for example during natural disasters, unfortunate incidents on the land, in the deepwater, or lakes. There were incidents happened to the search and rescue crew during the operation although they were well trained. A new method using robotic technology is important to reduce the crew's risk during operations. This research proposed a development of an autonomous surface vessel for search and rescue operations for deepwater applications. The proposed autonomous surface vessel is equipped with a global positioning system (GPS) and underwater sensor to search for the victims, black box, debris, or other evidence on the surface and underwater. The vessel was designed with monitoring and control via radio frequency wireless communication. The autonomous surface vessel prototype was developed and tested successfully with the telemetry at the ground station. The ground station acts as the control centre of the overall system. Results showed the vessel successfully operated autonomously. The operator at the ground station was able to monitor the sensor data and control the vessel's manoeuvre according to the created path. The telemetry coverage to monitor the water surroundings and control the vessel's manoeuvre was around 100 meters.

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A Blockchain-Enabled Approach for Online Stream Sensor Data Protection in Cyber-Physical Manufacturing Systems

10.1115/detc2021-72023 ◽

2021 ◽

Author(s):

Zhangyue Shi ◽

Chenang Liu ◽

Chen Kan ◽

Wenmeng Tian ◽

Yang Chen

Keyword(s):

Information Technologies ◽

Manufacturing Systems ◽

Rapid Development ◽

Data Access ◽

Sensor Data ◽

False Alarms ◽

Monitoring And Control ◽

Stream Data ◽

Physical Security ◽

And Control

Abstract With the rapid development of the Internet of Things and information technologies, more and more manufacturing systems become cyber-enabled, which significantly improves the flexibility and productivity of manufacturing. Furthermore, a large variety of online sensors are also commonly incorporated in the manufacturing systems for online quality monitoring and control. However, the cyber-enabled environment may pose the collected online stream sensor data under high risks of cyber-physical attacks as well. Specifically, cyber-physical attacks could occur during the manufacturing process to maliciously tamper the sensor data, which could result in false alarms or failures of anomaly detection. In addition, the cyber-physical attacks may also illegally access the collected data without authorization and cause leakage of key information. Therefore, it becomes critical to develop an effective approach to protect online stream data from these attacks so that the cyber-physical security of the manufacturing systems could be assured. To achieve this goal, an integrative blockchain-enabled method, is proposed by leveraging both asymmetry encryption and camouflage techniques. A real-world case study that protects cyber-physical security of collected stream data in additive manufacturing is provided to demonstrate the effectiveness of the proposed method. The results demonstrate that malicious tampering could be detected in a relatively short time and the risk of unauthorized data access is significantly reduced as well.

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Preliminary Design of Monitoring and Control Subsystem for GNSS Ground Station

Journal of Astronomy and Space Sciences ◽

10.5140/jass.2008.25.2.227 ◽

2008 ◽

Vol 25 (2) ◽

pp. 227-238

Author(s):

Seong-Kyun Jeong ◽

Jae-Eun Lee ◽

Han-Earl Park ◽

Sang-Uk Lee ◽

Jae-Hoon Kim

Keyword(s):

Preliminary Design ◽

Monitoring And Control ◽

Control Subsystem ◽

Ground Station ◽

And Control

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Evolution of the ESA Ground Station Monitoring and Control System

SpaceOps 2006 Conference ◽

10.2514/6.2006-5636 ◽

2006 ◽

Author(s):

Yves Doat ◽

Gerhard Theis ◽

Catherine Lannes

Keyword(s):

Control System ◽

Monitoring And Control ◽

Monitoring And Control System ◽

Ground Station ◽

And Control

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Design of a Ventilation Control System in Underground Mines and Tunnels

International Journal of Emerging Technology and Advanced Engineering ◽

10.46338/ijetae0921_09 ◽

2021 ◽

Vol 11 (9) ◽

pp. 73-81

Author(s):

Marcos Hernández VaraCadillo ◽

◽

Brian Meneses Claudio ◽

Alexi Delgado

Keyword(s):

Control System ◽

High Risk ◽

Human Life ◽

Underground Mines ◽

Monitoring And Control ◽

Monitoring And Control System ◽

Work Area ◽

Ventilation Monitoring ◽

Risk Event ◽

And Control

Abstract— Today no one is free of accidents, especially in high-risk work environments such as in-mine and/or tunnel work. It is quite common that in this type of high-risk activities and where evacuation accesses are distant from the area of operations, the response time plays an important role in the event of a dangerous event, which can materialize in an accident if necessary. you do not act quickly. Having a realtime ventilation monitoring and control system helps us as a tool to prevent a possible risk event. This control system, by constantly monitoring the ventilation inside the tunnel or inside the mine, can send us an alert to a web server that can be monitored through a computer and/or a smartphone that is on the surface when there is a lack of air, when the temperature rises considerably and the humidity begins to rise or the air flow is minimal then the system will activate an alert to the different monitoring or control devices. Additionally, this prototype contributes to saving energy because it will automate the switching on of the fans only in the presence of people in the work area. This prototype thus achieves real-time supervision and allows us to make the best decision when faced with an event that endangers human life in the workplace. Keywords—Temperature; esp-32; Arduino; air sensor, mine, ventilation, work safe

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Applications of Machine Learning in Process Monitoring and Controls of L-PBF Additive Manufacturing: A Review

Applied Sciences ◽

10.3390/app112411910 ◽

2021 ◽

Vol 11 (24) ◽

pp. 11910

Author(s):

Dalia Mahmoud ◽

Marcin Magolon ◽

Jan Boer ◽

M.A Elbestawi ◽

Mohammad Ghayoomi Mohammadi

Keyword(s):

Machine Learning ◽

Defect Detection ◽

In Situ Monitoring ◽

Sensor Data ◽

Learning Approaches ◽

Monitoring And Control ◽

In Situ Sensors ◽

Applications Of Machine Learning ◽

And Control

One of the main issues hindering the adoption of parts produced using laser powder bed fusion (L-PBF) in safety-critical applications is the inconsistencies in quality levels. Furthermore, the complicated nature of the L-PBF process makes optimizing process parameters to reduce these defects experimentally challenging and computationally expensive. To address this issue, sensor-based monitoring of the L-PBF process has gained increasing attention in recent years. Moreover, integrating machine learning (ML) techniques to analyze the collected sensor data has significantly improved the defect detection process aiming to apply online control. This article provides a comprehensive review of the latest applications of ML for in situ monitoring and control of the L-PBF process. First, the main L-PBF process signatures are described, and the suitable sensor and specifications that can monitor each signature are reviewed. Next, the most common ML learning approaches and algorithms employed in L-PBFs are summarized. Then, an extensive comparison of the different ML algorithms used for defect detection in the L-PBF process is presented. The article then describes the ultimate goal of applying ML algorithms for in situ sensors, which is closing the loop and taking online corrective actions. Finally, some current challenges and ideas for future work are also described to provide a perspective on the future directions for research dealing with using ML applications for defect detection and control for the L-PBF processes.

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Distributed Remote IoT Sensor Data Monitoring and Control through the ARTIK Cloud

The Journal of Korean Institute of Communications and Information Sciences ◽

10.7840/kics.2018.43.12.2100 ◽

2018 ◽

Vol 43 (12) ◽

pp. 2100-2106

Author(s):

Jum-Han Bae ◽

Jong Tae Kim

Keyword(s):

Sensor Data ◽

Data Monitoring ◽

Monitoring And Control ◽

And Control

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Multichannel adaptive deployment and reliable communication design for unmanned surface vessel

International Journal of Advanced Robotic Systems ◽

10.1177/1729881419891581 ◽

2020 ◽

Vol 17 (1) ◽

pp. 172988141989158

Author(s):

Qiyu Yin ◽

Yuezu Lv

Keyword(s):

Data Transmission ◽

Design Method ◽

Reliable Data ◽

Monitoring And Control ◽

Reliable Communication ◽

Sea Trial ◽

Switching Model ◽

Unmanned Surface Vessel ◽

And Control ◽

Surface Vessel

For the unmanned surface vessel in performing military missions, the safety and controllability are two basic requirements, which need reachable communication channel and reliable data transmission. This article proposes an adaptive switching model with multichannel resource and the unmanned surface vessel shore-to-sea data intercommunication design method. The scheme adopts various mechanisms such as data space, standardized encapsulation, numbering and verification, and active/passive retransmission, which can ensure reliable data transmission and provide reliable communication information for unmanned surface vessel during autonomous mission. A sea trial is also carried out on the unmanned surface vessel control system based on the design scheme. Data analysis shows that the system can successfully realize communication switching and continuous data transformation, which is consistent with design expectation, and guarantees the continuous monitoring and control of unmanned surface vessel by shore-based control station.

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An Intelligent Robotic System Platform for Autonomous Mapping and Sensor Data Gathering of Non-GPS Friendly Environments

Dynamic Systems and Control, Parts A and B ◽

10.1115/imece2005-79140 ◽

2005 ◽

Author(s):

Agamemnon Crassidis ◽

Wayne W. Walter ◽

Douglas A. Carr ◽

Erin Long

Keyword(s):

Navigation System ◽

Data Gathering ◽

Robotic System ◽

Sensor Data ◽

Position Information ◽

Global Positioning ◽

Underwater Tunnel ◽

And Control ◽

Collapsed Building ◽

Dimensional Mapping

This paper presents results of a novel intelligent robotic system using a re-configurable platform for autonomous mapping and sensor data gathering of non-Global Positioning System (GPS) friendly, unknown and hazardous enclosed environments such as caves, underground and underwater tunnel networks, building floors, and spaces within a collapsed building rubble field. The work developed here forms a basis for a swarm of mini/micro robotic vehicles capable of autonomous routing and control with a self-contained navigation system that does not rely on GPS information. A robotic prototype capable of autonomously mapping a floor plan (such as hallways within a building) has been developed. The robot navigates autonomously without the use of GPS and gathers absolute position information developing a 2-dimensional map of the hallway network using a novel Mini Inertial Measurement/Navigation System (MIMNS) developed at RIT. Also, enhancements to the MIMNS unit are presented for estimating attitude orientation of the robot using an accelerometer based device allowing for non-flat plane mapping using the MIMNS unit. The paper presents the concepts of the robot hardware and software, results of a 2-dimensional mapping of a flat plane, and introduces simulation results of an accelerometer based attitude orientation device.

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Sensor Data Analysis On Monitoring And Control System Of Temperature And Humidity Based On Android In Soybean Seed Storage Room Using Nodemcu

JAICT ◽

10.32497/jaict.v3i1.1290 ◽

2019 ◽

Vol 3 (1) ◽

Author(s):

Sindung HW Sasono

Keyword(s):

Control System ◽

Data Analysis ◽

Soybean Seed ◽

Seed Storage ◽

Sensor Data ◽

Monitoring And Control ◽

Storage Room ◽

Temperature State ◽

Temperature And Humidity ◽

And Control

soybean seeds may be damaged during storage time. Temperature and humidity of soybean seed storage room, is one of the external factors of damage to the seed. The system consists of monitoring and control temperature and humidity in some rooms used as soybean seed storage room samples. This study discusses and perform sensor data analysis using several types of temperature and humidity sensors based on Internet of Things. Sensor nodes generate data and processed by a microcontroller NodeMCU ESP8266, and the results data is then transmitted by the Internet network using MQTT broker and stored in the database. Results data is then analyzed to monitor the condition of soybean seed storage room. SHT30 sensor has the most excellent temperature accuracy of 98, 21%. DHT22 sensor has the most excellent moisture accuracy of 95.74%. Data sending to the database has a good level of dataloss category for node 1 is 3.39%, 4.33% for node 2, and 3.22% for node 3. Air conditioner control system using Android can keep the room temperature state in the range of 18-23oC and humidity of 40-60% with an air conditioning remote control setting at 20oC on an area of 36 m2.

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