Smart system for monitoring ammonium nitrate storage warehouse

Ibrahim, Maha K.; Hussien, Nadia Mahmood; Alsaad, Saad Najim

doi:10.11591/ijeecs.v23.i1.pp583-589

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…With NumPy and Python, you can look at the structure of OpenCV's arrays. We use vector space to find the parts of an image pattern (Ibrahim et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

Intelligent Image Processing System Based on Virtual Painting

Hussain

2023

JLMA

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Image processing and artificial intelligence have come so far in the age of technology that they are now used in every field. AI is meant to help people do their jobs better and with less help. Virtual painting is a clever tool that lets us paint by just moving our hands. This app uses hand tracing and finger movement recording to show marks. With this program, we can open the camera on our computer or laptop and draw with our hands, colored pens, or pens we made ourselves. Image processing is used to figure out how the hand is moving. This turns the person in front of the camera into a great illustrator who can pick out colors and draw in similar directions on the screen. OpenCV, which is the brain of the system, and Media Pipe have been added to this application.

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“…With NumPy and Python, you can look at the structure of OpenCV's arrays. We use vector space to find the parts of an image pattern (Ibrahim et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

Intelligent Image Processing System Based on Virtual Painting

Hussain

2023

JLMA

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“…In 2021, Maha Khalil Ibrahim et al [20] developed an intelligent system for monitoring the storage of ammonium nitrate. Their system has three components: The Warehouse Monitoring Part (WMP), the Chemical Control System (MCS) part, and the third part is the Emergency Part (EP).…”

Section: Related Workmentioning

confidence: 99%

Smart Chemical Material Store System Using IOT and Raspberry PI

2024

IJSER

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Within the period of savvy innovation, the administration of chemical capacity postures critical challenges, especially in guaranteeing security and natural compliance. This paper plan and usage of a keen chemical capacity framework utilizing Raspberry PI presents an imaginative arrangement to this squeezing issue by leveraging the capabilities of Raspberry PI4 and the Web of Things (WoT) innovation. This investigate expresses the advancement and sending of a exceedingly productive, cost-effective shrewd chemical capacity framework outlined to optimize security, energy saving and protecting the internal and external environment of the store from air pollution. By coordination sensors for identifying different chemical gasses, temperature, mugginess, and pH levels, washing column, the framework gives real-time information examination, guaranteeing a responsive and energetic approach to chemical capacity administration. The Raspberry PI4 serves as the central handling unit, coordinating information procurement, processing, and decision-making forms to preserve ideal capacity conditions and preemptively address potential risks. Through the utilization of K-Means Calculation for information investigation, the framework illustrates extraordinary capability in recognizing and cautioning to dangerous conditions, in this way essentially decreasing the hazard of chemical mischances and processed. The usage exhibits a versatile, versatile system that obliges the expansion of different sensors and gadgets, encouraging a comprehensive observing arrangement custom-made to the particular needs of chemical capacity offices. This investigate not only contributes to the field of chemical security but moreover sets a point of reference for the application of savvy advances in mechanical security administration, advertising experiences and techniques that can be adjusted over assorted segments.

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“…The system in [19] using different gas sensors, monitors gas concentration and temperature in a biogas reactor. The smart system proposed by [20] was capable of sensing ammonium nitrate that could lead to fire and explosion in storage warehouses. Applications of e-noses outside these three main domains also involve explosive detection [21] and the space industry [22].…”

Section: Introductionmentioning

confidence: 99%

Reliable e-nose for air toxicity monitoring by filter diagonalization method

Macias-Quijas

Velazquez

Fazio

et al. 2022

IJECE

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This paper introduces a compact, affordable electronic nose (e-nose) device devoted to detect the presence of toxic compounds that could affect human health, such as carbon monoxide, combustible gas, hydrogen, methane, and smoke, among others. Such artificial olfaction device consists of an array of six metal oxide semiconductor (MOS) sensors and a computer-based information system for signal acquisition, processing, and visualization. This study further proposes the use of the filter diagonalization method (FDM) to extract the spectral contents of the signals obtained from the sensors. Preliminary results show that the prototype is functional and that the FDM approach is suitable for a later classification stage. Example deployment scenarios of the proposed e-nose include indoor facilities (buildings and warehouses), compromised air quality places (mines and sanitary landfills), public transportation, mobile robots, and wireless sensor networks.

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Smart system for monitoring ammonium nitrate storage warehouse

Cited by 4 publications

References 19 publications

Intelligent Image Processing System Based on Virtual Painting

Intelligent Image Processing System Based on Virtual Painting

Smart Chemical Material Store System Using IOT and Raspberry PI

Reliable e-nose for air toxicity monitoring by filter diagonalization method

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