IoT Based Automated Greenhouse Monitoring System

Danita, M.; Mathew, Blessy; Shereen, Nithila; Sharon, Namrata; Paul, J. John

doi:10.1109/iccons.2018.8662911

Cited by 59 publications

(25 citation statements)

References 5 publications

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“…There are some common models utilized for this purpose, such as LP PYRA 02 [4], E+E Elektronik EE160 [18], DHT11 [19,20], and LM35 model [21]. On the other hand, Humidity sensors can be utilized for sensing the amount of vapours in the air, such as LP PYRA 02 [4], E+E Elektronik EE160 [18], DHT11 [19,20], and HSM20G [21]. Additionally, there is another important sensing technology need to be utilized inside the greenhouse for measuring the level of CO 2 .…”

Section: A Iot Sensorsmentioning

confidence: 99%

“…End-users can access these data from any active internet device and gain benefits of the generated knowledge regarding their greenhouse crops production, energy consumption, and other related issues associated to this business [12][13][14]. The use of IoT in greenhouses is receiving increasing attention and many interesting results have been achieved [15][16][17]. In this paper, based on the IoT new advances in using sensors equipment, we propose to build an intelligent Energy-Efficient (EE) system which monitors and controls internal greenhouse temperature.…”

Section: Introductionmentioning

confidence: 99%

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An Intelligent IoT-Based System Design for Controlling and Monitoring Greenhouse Temperature

2020

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The Kingdom of Saudi Arabia is known for its extreme climate where temperatures can exceed 50 °C, especially in summer. Improving agricultural production can only be achieved using innovative environmentally suitable solutions and modern agricultural technologies. Using Internet of Things (IoT) technologies in greenhouse farming allows reduction of the immediate impact of external climatic conditions. In this paper, a highly scalable intelligent system controlling, and monitoring greenhouse temperature using IoT technologies is introduced. The first objective of this system is to monitor the greenhouse environment and control the internal temperature to reduce consumed energy while maintaining good conditions that improve productivity. A Petri Nets (PN) model is used to achieve both monitoring of the greenhouse environment and generating the suitable reference temperature which is sent later to a temperature regulation block. The second objective is to provide an Energy-Efficient (EE) scalable system design that handles massive amounts of IoT big data captured from sensors using a dynamic graph data model to be used for future analysis and prediction of production, crop growth rate, energy consumption and other related issues. The design tries to organize various possible unstructured formats of raw data, collected from different kinds of IoT devices, unified and technology-independent fashion using the benefit of model transformations and model-driven architecture to transform data in structured form.

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Section: A Iot Sensorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Intelligent IoT-Based System Design for Controlling and Monitoring Greenhouse Temperature

2020

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“…This way is straightforward and easy to implement but still affected by noisy data. Its contribution to the performance of the model is limited [29,30] because it depends on the data purity and special requirement of task.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Sensor Data Pre-Processing Methodology for the Internet of Things Using Anomaly Detection and Transfer-By-Subspace-Similarity Transformation

Zhong

Fong

et al. 2019

Sensors

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The Internet of Things (IoT) and sensors are becoming increasingly popular, especially in monitoring large and ambient environments. Applications that embrace IoT and sensors often require mining the data feeds that are collected at frequent intervals for intelligence. Despite the fact that such sensor data are massive, most of the data contents are identical and repetitive; for example, human traffic in a park at night. Most of the traditional classification algorithms were originally formulated decades ago, and they were not designed to handle such sensor data effectively. Hence, the performance of the learned model is often poor because of the small granularity in classification and the sporadic patterns in the data. To improve the quality of data mining from the IoT data, a new pre-processing methodology based on subspace similarity detection is proposed. Our method can be well integrated with traditional data mining algorithms and anomaly detection methods. The pre-processing method is flexible for handling similar kinds of sensor data that are sporadic in nature that exist in many ambient sensing applications. The proposed methodology is evaluated by extensive experiment with a collection of classical data mining models. An improvement over the precision rate is shown by using the proposed method.

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“…The wheat crop has quite different temperatures. The ideal growing temperature of the wheat crop is between 10º C and 24 º C. The minimum temperature should not be less than 3º C and not exceed 33º C [13]- [14].…”

Section: F Wheat Cropmentioning

confidence: 99%

Performance Assessment of Solar Powered Smart Drip Irrigation System using Arduino

Pugalhanthi,

Kumar,

Kumar

et al. 2019

IJEAT

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In the agriculture field, the method of irrigation and its proper usage is more important and it is well known that a very economical and efficient method is drip irrigation. The continuous monitoring of the soil and weather condition has to be done by the farmer in favour of growth of crops in conventional drip irrigation system. In this proposed system, the soil and weather condition of the field are monitored by the moisture as well as temperature sensor. The values from the temperature and moisture sensors are sensed and the signal is sent to the Arduino IDE controller which is powered by solar energy and thus the present values are compared with predefined values. According to value of the temperature and moisture, the crops can be supplied with the required amount of water. In the liquid crystal display, the sensed values of the temperature and moisture will be displayed and the user can receive the data through the GSM module.

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IoT Based Automated Greenhouse Monitoring System

Cited by 59 publications

References 5 publications

An Intelligent IoT-Based System Design for Controlling and Monitoring Greenhouse Temperature

An Intelligent IoT-Based System Design for Controlling and Monitoring Greenhouse Temperature

A Novel Sensor Data Pre-Processing Methodology for the Internet of Things Using Anomaly Detection and Transfer-By-Subspace-Similarity Transformation

Performance Assessment of Solar Powered Smart Drip Irrigation System using Arduino

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