Building a Fish–Vegetable Coexistence System Based on a Wireless Sensor Network

Hsiao, Sung-Jung; Sung, Wen‐Tsai

doi:10.1109/access.2020.3032795

Cited by 15 publications

(11 citation statements)

References 28 publications

(21 reference statements)

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“…The authors used self-adaptive data fusion via a wireless sensors network to remotely monitor the medical care control system. The results of experiments showed that the system can enable the accurate and stable monitoring of the patient [24][25][26]. It can solve three pressing problems:…”

Section: Round Intersection Positioningmentioning

confidence: 99%

RFID Positioning and Physiological Signals for Remote Medical Care

Sung¹,

Hsiao²

2022

Computer Systems Science and Engineering

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The safety of patients and the quality of medical care provided to them are vital for their wellbeing. This study establishes a set of RFID (Radio Frequency Identification)-based systems of patient care based on physiological signals in the pursuit of a remote medical care system. The RFID-based positioning system allows medical staff to continuously observe the patient's health and location. The staff can thus respond to medical emergencies in time and appropriately care for the patient. When the COVID-19 pandemic broke out, the proposed system was used to provide timely information on the location and body temperature of patients who had been screened for the disease. The results of experiments and comparative analyses show that the proposed system is superior to competing systems in use. The use of remote monitoring technology makes user interface easier to provide high-quality medical services to remote areas with sparse populations, and enables better care of the elderly and patients with mobility issues. It can be found from the experiments of this research that the accuracy of the position sensor and the ability of package delivery are the best among the other related studies. The presentation of the graphical interface is also the most cordial among human-computer interaction and the operation is simple and clear.

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Section: Round Intersection Positioningmentioning

confidence: 99%

RFID Positioning and Physiological Signals for Remote Medical Care

Sung¹,

Hsiao²

2022

Computer Systems Science and Engineering

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“…These controllers will adjust their parameters according to the best living environment for the fish and achieve the most stable and comfortable state. This information is continuously stored in a computer database, allowing users to track and record the growth of their fish [6].…”

Section: Introductionmentioning

confidence: 99%

Aquarium Monitoring System Based on Internet of Things

Sung¹,

Tasi²,

Hsiao³

2022

Intelligent Automation &Amp; Soft Computing

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With the ever-increasing richness of social resources, the number of devices using the Internet of Things is also increasing. Currently, many people keep pets such as fish in their homes, and they need to be carefully taken care of. In particular, it is necessary to create a safe and comfortable environment for them and to maintain this environment continuously. An adverse environment can affect the growth of fish and may even result in their death. This study used the LinkIt 7697 module and the BlocklyDuino editor to produce a control system for a smart aquarium. The purpose of this system is to monitor the temperature, light intensity, and water level in an aquarium, as well as to provide alerts to presence of intruders; therefore, temperature, light, ultrasonic, and infrared sensing modules are used. The system has set aquarium environment thresholds, and it processes the signals obtained by the sensors to control and optimize the outputs to loads using data fusion calculations so that the aquarium has the most comfortable environment for the fish. An automatic feeder is also included in the system, and this uses a servo motor. The data from the system is uploaded to a back-end computer through the built-in Wi-Fi system of the LinkIt 7697 module. The Cloud Sandbox platform is used to display the results in real time, achieving the purpose of remote network monitoring.

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“…WSNs have sensor nodes of different displacements, which are displaced and isolated, wirelessly connected to each other, and usually connected to the gate nodes [15][16]. The distance between the sensor terminals can range from ten to hundreds of meters depending on the antenna gain, transmission power and operating frequency [17][18][19][20]. The wireless sensor senses the day-to-day weather in live data, which helps farmers monitor the weather.…”

Section: Introductionmentioning

confidence: 99%

Weather Prediction based on Wireless Sensor Network and Internet of Things with Analysis using Hybrid SSOA with MA

A.S.²

2022

Preprint

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Weather forecasting is a growing area that predicts the weather that will occur in a particular place at a particular time. Weather forecasting is considered to be the most important part of research where many real-time issues arise. These are the requirements for wireless sensor networks to detect the weather. In this article we propose using the Mayfly Algorithm (MA) hybrid algorithm with Shuffled Shepherd Optimization Algorithm (SSOA). Experimental tasks are carried out with a set of climate data. Based on climatic parameters such as temperature, humidity and clouds, the data is divided into heat, wind and rain. From the result obtained, it is predicted that the weather will prove the proposed qualification methods at the level of accuracy. The result shows that the hybridized SSOA and MA method is efficient and accurate in predicting weather conditions. This experimental result is carried out by using Wireless Sensors Network and IoT on agricultural land.

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Building a Fish–Vegetable Coexistence System Based on a Wireless Sensor Network

Cited by 15 publications

References 28 publications

RFID Positioning and Physiological Signals for Remote Medical Care

RFID Positioning and Physiological Signals for Remote Medical Care

Aquarium Monitoring System Based on Internet of Things

Weather Prediction based on Wireless Sensor Network and Internet of Things with Analysis using Hybrid SSOA with MA

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