Javad Pourqasem; Duško Tešić; Eisa Abdolmaleki
Abstract
Smart water for the quality monitoring is to be gaining in importance with a advancements in communication technology. The Web of Things (IoT) gets the associations among different gadgets with the capacity to trade and getting information. IoT additionally stretches out its ability to ecological issues ...
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Smart water for the quality monitoring is to be gaining in importance with a advancements in communication technology. The Web of Things (IoT) gets the associations among different gadgets with the capacity to trade and getting information. IoT additionally stretches out its ability to ecological issues notwithstanding the computerization industry by utilizing industry 4.0. As water is one of the fundamental necessities of human endurance, it is expected to consolidate some instruments to screen water quality from the opportunity to time. Around 45% of passing’s are caused because of defiled water on the planet. Subsequently, there is a need to guarantee the supply of filtered drinking water for individuals both in urban areas and towns. Water Quality Monitoring is a practical and proficient framework intended to screen drinking water quality that utilizes Internet of Things (IoT) innovation. In this paper, the proposed framework comprises a few sensors to gauge different boundaries, for example, pH esteem, and turbidity in the water, level of water in the tank, temperature, and mugginess of the encompassing air. And for more, information the Microcontroller Unit (MCU) is connected to these sensors and handled with a Personal Computer (PC). The got information is shipped off the cloud by utilizing IoT based Think Speak application to screen the nature of the water.
Shahed Mohammadi; Niloufar Hemati; Neda Mohammadi
Abstract
In today's world, where speech recognition has become an integral part of our daily lives, the need for systems equipped with this technology has increased dramatically in the past few years. This research aims to locate the two selected Persian words in any given audio file. For this purpose, two standard ...
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In today's world, where speech recognition has become an integral part of our daily lives, the need for systems equipped with this technology has increased dramatically in the past few years. This research aims to locate the two selected Persian words in any given audio file. For this purpose, two standard and native datasets were prepared for this model one for train and the other for the test. Both datasets were converted into images of audio waveforms. Using the object detection technique, the model could extract different bounding boxes for each test audio, and then each box image goes through a CNN classifier and returns a corresponding label. Finally, a threshold is set so that only boxes with high accuracy are displayed as output. The results showed 93% accuracy for the CNN classifier and 50% accuracy for testing the model with object detection.
Aziza Algarni
Abstract
Parking a vehicle in dense traffic environments often leads to excessive driving time in search of free space, which leads to congestion and environmental pollution. Lack of guidance information about vacant parking spaces is one reason for inefficient parking behavior. Smart parking sensors and technologies ...
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Parking a vehicle in dense traffic environments often leads to excessive driving time in search of free space, which leads to congestion and environmental pollution. Lack of guidance information about vacant parking spaces is one reason for inefficient parking behavior. Smart parking sensors and technologies facilitate the guidance of drivers to free parking spaces, thereby improving parking efficiency. Currently, no such sensors or technologies are used for the open parking lot. This study reviews the literature on the usage of smart parking sensors, technologies, and applications and evaluates their applicability to open parking lots. To develop smart parking applications for open parking lots, further research is needed in deep learning and multi-agent systems.
