Object detection and position tracking in real time using Raspberry Pi

Anand, G.; Kumawat, Ashok Kumar

doi:10.1016/j.matpr.2021.06.437

Cited by 24 publications

(10 citation statements)

References 5 publications

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“…Deep learning is a branch of AI; a CNN is one of the most common deep learning techniques [35]. CNNs have been widely applied to object detection and image recognition [3]. Deep learning and Raspberry Pi technologies are used for the internet of things (IoT) [27].…”

Section: Research Methodology Based On Dt–pblmentioning

confidence: 99%

Enhancing design thinking in engineering students with project‐based learning

Jiang

Pang

2023

Comp Applic In Engineering

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Modern society requires increasing creative talents. As an educational concept, design thinking (DT) has been successfully applied in education to foster innovation. However, educational research on improving the engineering design ability of engineering students through the design process and practice is limited. Research has shown that project-based learning (PBL) is an effective engineering education method. This research integrates DT and PBL (DT-PBL) in teaching the course "Introduction to Artificial Intelligence and Basic Algorithm Training" and discusses the teaching method and implementation of DT-PBL in detail through an example of a comprehensive training project of software and hardware collaboration based on a convolutional neural network and Raspberry Pi. This study considers the impact of DT-PBL on engineering students in terms of learning motivation and creativity using the pretest and posttest mixed method. Data analysis of quantitative tests and qualitative interviews shows that (1) The experimental group is superior to the comparison group in terms of overall learning motivation. Through a comprehensive training project of software and hardware collaboration, students can reflect on the required professional knowledge and skills, and improve their DT, engineering application, and innovation abilities and (2) The experimental group was superior to the comparison group in terms of overall creativity (adventure, curiosity, imagination, and challenge). Students in the experimental group can think more quickly and put forth more creative ideas from the perspective of user needs.

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Section: Research Methodology Based On Dt–pblmentioning

confidence: 99%

Enhancing design thinking in engineering students with project‐based learning

Jiang

Pang

2023

Comp Applic In Engineering

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“…Anand, G and Kumawat, A.K . [12] have described an e cient method for object identi cation based on shape and its displacement in real time using the OpenCV library of programming roles primarily intended for computer vision and Raspberry Pi with camera module to help computers "see" and recognise information contained in digital images, for example videos and photographs. In [13], the authors introduced a new methodology for counting moving people and detecting directions using convolutional neural networks (CNNs) and generative adversarial networks (GANs), a detection system based on a pyroelectric infrared (PIR) sensor.…”

Section: Related Workmentioning

confidence: 99%

Using IoT and YOLOv5 for real-time security monitoring of homes

NOUTELE

2024

Preprint

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Everyone wants their home to be as secure as possible against disturbances and threats. Many people have installed Closed Circuit Television (CCTV) as a home security system. Apart from the fact that it is relatively expensive to install, CCTV has shortcomings that make it difficult to integrate with stable, secure user devices in real time. The aim of this work is to develop a security system capable of detecting malicious people in a house using a Raspberry PI 3, infrared (PIR) and ultrasound sensors, a webcam for taking photos and YOLOv5 for detecting objects. Once the malicious person is detected, the homeowner is immediately informed of the status of their home on their mobile phone via the Telegram mobile application. This proposed system can be applied and used as a safe and very inexpensive means of prevention.

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“…Untuk proses image processing menggunakan Raspberry Pi 4B. Komponen kamera berperan penting untuk mengambil gambar berupa video menggunakan Raspberry Pi Camera V2, sehingga penerapannya menjadi lebih mudah [15].…”

Section: Pendahuluanunclassified

Penerapan Deteksi Garis Pada Agv Menggunakan Metode HSV

Saputra,

Setiawan

2023

Transmisi J.Ilm. Tek. Elekt.

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Dalamperkembangan teknologisaatini,khususnya disektorindustri,robotdengankecerdasanbuatanmengemban peranpentingdalammeningkatkan efisiensiwaktukerjamanusia.PenelitianinimenciptakansebuahrobotAGVyang dilengkapisistemkecerdasanbuatan,menggunakan kamerasebagaisensorvisualuntukmendeteksi garislintasan sebagaipanduannavigasi.RobotAGVinimemanfaatkanOpenCVuntukpemrosesancitradenganmetodefilterwarna HSV.Metodeinimencakup teknikmorfologi danGaussianbluruntukmengenali garislintasanyangakandilalui. Setelah prosesidentifikasijalur, robot AGV akan bergerak sesuai jalur yang terdeteksioleh kamera.Pengujian perangkatkeras dilakukandi laboratorium,bahwamodenavigasirobotAGV berdasarkanmetode HSV mampu berfungsibaikdanmenghasilkantingkatakurasideteksijaluryangtinggi.

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Object detection and position tracking in real time using Raspberry Pi

Cited by 24 publications

References 5 publications

Enhancing design thinking in engineering students with project‐based learning

Enhancing design thinking in engineering students with project‐based learning

Using IoT and YOLOv5 for real-time security monitoring of homes

Penerapan Deteksi Garis Pada Agv Menggunakan Metode HSV

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