Exploiting IoT and Its Enabled Technologies for Irrigation Needs in Agriculture

Veerachamy, Ramachandran; Ramalakshmi, R.; Kavin, Balasubramanian Prabhu; Hussain, Irshad; Almaliki, Abdulrazak H.; Almaliki, Abdulrhman A.; Elnaggar, Ashraf Y.; Hussein, Enas E.

doi:10.3390/w14050719

Cited by 67 publications

(31 citation statements)

References 68 publications

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“…The left side of the figure shows an example of the state after one round of cost function calculation, the gray dots and black dots are the pixel points for which the cost function has been calculated, the gray dots are the points in the region, and the black dots are the edge points [ 24 – 29 ]. The white dots are the pixel points for which the cost function has not been computed yet.…”

Section: Analysis Of Convolutional Neural Network and 3d Magnetic Res...mentioning

confidence: 99%

Design of a Classification Recognition Model for Bone and Muscle Anatomical Imaging Based on Convolutional Neural Network and 3D Magnetic Resonance

Pan

Yang

2022

Applied Bionics and Biomechanics

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In this paper, we use convolutional neural networks to conduct in-depth research and analysis on the classification and recognition of bone and muscle anatomical imaging graphics of 3D magnetic resonance and design corresponding models for practical applications. A series of medical image segmentation models based on convolutional neural networks is proposed. In this paper, firstly, a separated attention mechanism is introduced in the model, which divides the input data into multiple paths, applies self-attention weights to adjacent data paths, and finally fuses the weighted values to form the basic convolutional block. This structure has multiple parallel data paths, which increases the width of the network and therefore improves the feature extraction capability of the model. Then, this paper proposes a bidirectional feature pyramid for medical image segmentation task, which has top-down and bottom-up data paths, and, together with jump connections, can fully interact with feature maps at different scales. After that, a new activation function Mish is introduced, and its advantages over other activation functions are experimentally demonstrated. Finally, for the situation that medical image annotations are not easy to obtain, a semisupervised learning method is introduced in the model training process, and the effectiveness of this method is experimentally demonstrated. The joint network first denoises the input image, then super-resolution mapping is performed on the noise-removed feature map, and finally, the super-resolution 3D-MR image is obtained. We update the network by combining the denoising loss and super-resolution loss during the joint network training process. The experimental results show that the joint network with denoising first and then super-resolution outperforms the joint network with other task order and outperforms the method that performs the two tasks separately and the proposed method in this paper has the optimal performance.

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Section: Analysis Of Convolutional Neural Network and 3d Magnetic Res...mentioning

confidence: 99%

Design of a Classification Recognition Model for Bone and Muscle Anatomical Imaging Based on Convolutional Neural Network and 3D Magnetic Resonance

Pan

Yang

2022

Applied Bionics and Biomechanics

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“…• Ground truth content caching method In this method, the most popular contents are cached in differen transmitters without predicting the popularity of contents [42,46].…”

Section: Performance Comparison Of Different Proactive Content Cachin...mentioning

confidence: 99%

Proactive Caching in D2D Assisted Multitier Cellular Network

Ahmad

Hussain

et al. 2022

Sensors

Self Cite

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Cache-enabled networks suffer hugely from the challenge of content caching and content delivery. In this regard, cache-enabled device-to-device (D2D) assisted multitier cellular networks are expected to relieve the network data pressure and effectively solve the problem of content placement and content delivery. Consequently, the user can have a better opportunity to get their favored contents from nearby cache-enabled transmitters (CETs) through reliable and good-quality links; however, as expected, designing an effective caching policy is a challenging task due to the limited cache memory of CETs and uncertainty in user preferences. In this article, we introduce a joint content placement and content delivery technique for D2D assisted multitier cellular networks (D2DMCN). A support vector machine (SVM) is employed to predict the content popularity to determine which content is to be cached and where it is to be cached, thereby increasing the overall cache hit ratio (CHR). The content request is satisfied either by the neighboring node through the D2D link or by the cache-enabled base stations (BSs) of the multitier cellular networks (MCNs). Similarly, to solve the problem of optimal content delivery, the Hungarian algorithm is employed aiming to improve the quality of satisfaction. The simulation results indicate that the proposed content placement strategy effectively optimizes the overall cache hit ratio of the system. Similarly, an effective content delivery approach reduces the request content delivery delay and power consumption.

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“…Improvements [25] Using an automatic food dispenser for fish feeding can cause overfeeding the fish and wastage of consuming the food.…”

Section: Previous Workmentioning

confidence: 99%

“…A considerable amount of literature has been published on automatic aquaponic systems. In 2020, a smart and sustainable home aquaponic system was developed to resolve the issue of food security that has been recurring for years in Singapore [25]. This project was designed for a home-based environment aquaponic system to encourage local citizens to produce their own food.…”

Section: Introductionmentioning

confidence: 99%

Smart Automation Aquaponics Monitoring System

Abdullah

Mazalan

2022

JOIV : Int. J. Inform. Visualization

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Modern agriculture, such as aquaponics, has become a well-known solution nowadays for farming, especially in Asia countries. It provides an alternative to support food demands and maintain environmental sustainability. However, it requires manpower and time to maintain and monitor the system. This research proposes a smart automation aquaponic monitoring system that helps users maintain and monitor the system through smartphone applications. The system uses DHT11 to record temperature and humidity, HC-SR04 for water level, and FC-28 to maintain soil moisture. The sensors are integrated with WeMos D1 Wi-Fi Uno based ESP8266 microcontroller to process the data. The data collected is stored in the cloud and retrieved via the Blynk application, which also performs as an actuator and allows users to control the parameters involved. The application helps to monitor the humidity, temperature, and water level in the fish tank and control the actuator for feeding fish. The system also sends a notification to the user for any activities performed, such as watering plants, feeding fish, and abnormality of temperature in the surroundings. The performance of the system was evaluated using regression modeling. The result indicates positive growth for both plants and fish during the monitoring duration, suggesting the proposed system's effectiveness. Overall, this solution helps to reduce manpower and operation costs as well as alternatives for food demand and stabilize environmental sustainability, especially in the urban residency.

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Exploiting IoT and Its Enabled Technologies for Irrigation Needs in Agriculture

Cited by 67 publications

References 68 publications

Design of a Classification Recognition Model for Bone and Muscle Anatomical Imaging Based on Convolutional Neural Network and 3D Magnetic Resonance

Design of a Classification Recognition Model for Bone and Muscle Anatomical Imaging Based on Convolutional Neural Network and 3D Magnetic Resonance

Proactive Caching in D2D Assisted Multitier Cellular Network

Smart Automation Aquaponics Monitoring System

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