Intelligent Agriculture Greenhouse Environment Monitoring System Based on IOT Technology

Dan, Liu; Xin, Cao; Chongwei, Huang; Ji, Liangliang

doi:10.1109/icitbs.2015.126

Cited by 129 publications

(43 citation statements)

References 1 publication

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“…Specifically, the system can be applied to health care facilities, such as nursing homes and hospices, to prevent environmental air pollution from adversely affecting people's health. (7) Traditional air quality information is dependent on the observatory's detection and announcement. In this work, we hope to extend the application by using portable air boxes to detect air quality and provide real-time announcements via the smart iAIR system on a cloud service platform.…”

Section: Related Workmentioning

confidence: 99%

Smart iAIR System with Integration of the Internet of Things and Mobile Applications

Chang¹,

Tsai²,

Kuo³

et al. 2019

Sensors and Materials

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Commercially available crowdsourced air boxes have nonuniform distributions and cannot achieve suitable observation densities. As a result, current air quality data are limited to the vicinity of an observation station, rather than providing accurate actual data around a user. In this research, we propose the implementation of iAIR air pollution detection air boxes, which can be installed on air purifiers or air conditioners in large numbers and distributed over a wide area; this provides a real-time air pollution information map according to various air qualities and shows a higher resolution. The provided real-time information enables a user to immediately take appropriate response measures once poor air quality has been detected. When air quality degrades or the user's heart rate exceeds the normal range, the smart iAIR system installed on a cloud service platform will transmit warning messages to a mobile app and a wearable personal smart wristband, and at the same time, activate the air purifier (or air conditioner) to improve the current air quality and advise the user to move to an environment with better air quality with guidance by an air navigation map.

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Section: Related Workmentioning

confidence: 99%

Smart iAIR System with Integration of the Internet of Things and Mobile Applications

Chang¹,

Tsai²,

Kuo³

et al. 2019

Sensors and Materials

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show abstract

“…Perception layer: Perception layer is mainly to achieve data acquisition and perception [15,16] including citrus soil moisture and temperature, air humidity and temperature, soil nutrients and sensor space coordinate. According to the experiment, we found that the temperature and humidity at different soil depths at the same location can better reflect the environmental condition.…”

Section: Overall Structurementioning

confidence: 99%

Monitoring Citrus Soil Moisture and Nutrients Using an IoT Based System

Zhang

et al. 2017

Sensors

119

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Chongqing mountain citrus orchard is one of the main origins of Chinese citrus. Its planting terrain is complex and soil parent material is diverse. Currently, the citrus fertilization, irrigation and other management processes still have great blindness. They usually use the same pattern and the same formula rather than considering the orchard terrain features, soil differences, species characteristics and the state of tree growth. With the help of the ZigBee technology, artificial intelligence and decision support technology, this paper has developed the research on the application technology of agricultural Internet of Things for real-time monitoring of citrus soil moisture and nutrients as well as the research on the integration of fertilization and irrigation decision support system. Some achievements were obtained including single-point multi-layer citrus soil temperature and humidity detection wireless sensor nodes and citrus precision fertilization and irrigation management decision support system. They were applied in citrus base in the Three Gorges Reservoir Area. The results showed that the system could help the grower to scientifically fertilize or irrigate, improve the precision operation level of citrus production, reduce the labor cost and reduce the pollution caused by chemical fertilizer.

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“…deployed in agricultural production sites and wireless communication networks to realize intelligent perception, intelligent early warning, intelligent decision-making, intelligent analysis, expert online guidance, etc.in agricultural production environment, and provide accurate planting, visual management, intelligent decision making for agricultural production. Wisdom agriculture solutions based on WSN technology (Zigbee) have been widely used because of low cost, simple control and convenient to network [1][2][3]. At the same time, there are some shortcomings.…”

Section: Introductionmentioning

confidence: 99%

Research on Data Sparse-Collection and Transmission System for WSN Based on NB-IoT and FPGA

Sun¹,

Xu²,

Zheng³

2019

International Journal of Advanced Research in Computer and Comm

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This paper designs and implements a data sparse-acquisition and transmission system for Wireless Sensor Network (WSN) based on Narrow Band-Internet of Things (NB-IoT) and Field-Programmable Gate Array (FPGA) for smart agriculture. The use of distributed wireless network nodes to collect agricultural environment information in a sparse sampling manner can overcome the disadvantages of limited bandwidth and significantly reduce the amount of data transmission, thereby helping to reduce the energy consumption of wireless network nodes and extend the use time. We use FPGA as the base station to receive the data collected by each node, and make full use of the advantages of parallel computing in FPGA for data recovery. And the method we used are matrix filling algorithm, which was named Latent Factor Model (LFM) in the recommendation system, and gradient descent algorithm. Finally, the recovered complete data will be transmitted to the cloud platform for display in the way of NB-IoT. NB-IoT is an emerging Wide Area Network (WAN) technology that has the advantages of supporting massive connections and being geographically unrestricted. The results show that the data can be perfectly recovered within the specified error range, and the algorithm runs nearly three times faster than the serial operation after adding parallel operations.

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Intelligent Agriculture Greenhouse Environment Monitoring System Based on IOT Technology

Cited by 129 publications

References 1 publication

Smart iAIR System with Integration of the Internet of Things and Mobile Applications

Smart iAIR System with Integration of the Internet of Things and Mobile Applications

Monitoring Citrus Soil Moisture and Nutrients Using an IoT Based System

Research on Data Sparse-Collection and Transmission System for WSN Based on NB-IoT and FPGA

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