Ultrasonic Wireless Sensor Network for Human Habitation in Deep Space Mission

Kesuma, Hendra; Ahmadi-Pour, Sallar; Zimmerman, Hans-Jurgen; Joseph, Amber; Weis, Patrick

doi:10.1109/wisee.2019.8920364

Cited by 6 publications

(2 citation statements)

References 5 publications

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“…The ultrasonic sensor is an electronic device that will allow us to calculate the corresponding distance between the drone and the recyclable solid waste by using ultrasonic waves that are sent by the head and receive a reflected wave that returns from the impacted object, counting the time from the moment of transmission and reception. With this, it simplifies the user who manages the system with showing the value of the corresponding distance between both points, on the other hand, the advantages of this sensor is its low operating voltage and its low cost in the market, in addition to presenting a good accuracy that allows measuring distances from 2 to 450 cm [21].…”

Section: B Ultrasonic Sensormentioning

confidence: 99%

Image Processing System for the Detection of Recyclable Solid Waste

Meneses-Claudio¹,

Muñoz²,

Huamaní³

et al. 2023

IJETAE

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One of the problems that affects everyone is solid waste pollution, which has spread to various parts of the surface and has put the planet in trouble because of the enormous amount of waste that has accumulated over time, affecting the habitats of various marine and terrestrial animals. These damages on the environment, reflect the lack of culture human about recycling, just 10% worldwide recyclemore frequently in homes. Nowadays, the change of materials to biodegradable has been made so that their decomposition is early, accumulations of recyclable materials are still observed in various parts of the surface and observing that it does not solve the contamination. With the exposure of this problem, this article developed an image processing system for the detection of recyclable solid waste that through an automatic analysis will allow the identification of recyclable solid waste materials, such as plastic, cardboard and glass bottles, helping to detect those solid waste that canbe reuse and avoid accumulation of them per ton. Through its development, it was observed that the system identifies the various recyclable materials that are distributed throughout the street with an efficiency of 97.99%, standing out for its efficiency and precision in the analysis of recyclable materials.

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Section: B Ultrasonic Sensormentioning

confidence: 99%

Image Processing System for the Detection of Recyclable Solid Waste

Meneses-Claudio¹,

Muñoz²,

Huamaní³

et al. 2023

IJETAE

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“…Traditional approaches to anomaly detection frequently rely on cloud-based technologies that send data from edge devices to distant servers for examination. Although these cloud-centric strategies have shown to be successful in a variety of situations, they do have some drawbacks when used with IIoT applications [2]. Latency is one of the main issues with IIoT cloudbased anomaly detection.…”

Section: Introductionmentioning

confidence: 99%

Edge-Based Real-Time Sensor Data Processing for Anomaly Detection in Industrial IoT Applications

Deshpande,

Rahman

2023

RJCSE

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The Industrial Internet of Things (IIoT), which uses devices with sensors to provide real-time insights into crucial processes, has completely changed how industries function. However, there are many problems associated with the sheer volume and speed of data created in industrial environments, particularly when it comes to anomaly detection. The development of edge-based real-time sensor data processing techniques was required because traditional cloud-based solutions frequently experience latency problems and privacy issues. This study suggests a novel method for IIoT applications that focuses on processing sensor data at the edge, close to the data source, for anomaly identification. We offer real-time analysis of sensor data without the need for continuous data transfer to the cloud by utilising the processing capabilities of edge devices, such as industrial gateways and embedded systems. To find anomalies in streams of real-time sensor data, our methodology integrates data pre-processing, feature engineering, and machine learning algorithms. This strategy not only lessens the strain on the network's bandwidth but also ensures quick reaction to urgent situations, cutting downtime and boosting operational effectiveness. Proposed system has adaptive learning features that enable it to continuously adjust to altering ambient factors and sensor properties, enhancing the precision of anomaly detection over time. We provide experimental findings that show how our edge-based anomaly detection system performs well in diverse industrial situations. The results show that, while protecting data privacy and minimising latency, our methodology outperforms conventional cloud-based methods in terms of anomaly detection performance.

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Optimization and Solution Approaches in Utilizing Wireless Sensor Networks for Exploring Moon, Planets, and Space

Özkan

2022

Springer Optimization and Its Applications

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Ultrasonic Wireless Sensor Network for Human Habitation in Deep Space Mission

Cited by 6 publications

References 5 publications

Image Processing System for the Detection of Recyclable Solid Waste

Image Processing System for the Detection of Recyclable Solid Waste

Edge-Based Real-Time Sensor Data Processing for Anomaly Detection in Industrial IoT Applications

Optimization and Solution Approaches in Utilizing Wireless Sensor Networks for Exploring Moon, Planets, and Space

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