Internet of Plants Application for Smart Agriculture

Abstract

Abstract-Nowadays, Internet of Things (IoT) is receiving a great attention due to its potential strength and ability to be integrated into any complex system. The IoT provides the acquired data from the environment to the Internet through the service providers. This further helps users to view the numerical or plotted data. In addition, it also allows objects which are located in long distances to be sensed and controlled remotely through embedded devices which are important in agriculture domain. Developing such a system for the IoT is a very complex task due to the diverse variety of devices, link layer technologies, and services. This paper proposes a practical approach to acquiring data of temperature, humidity and soil moisture of plants. In order to accomplish this, we developed a prototype device and an android application which acquires physical data and sends it to cloud. Moreover, in the subsequent part of current research work, we have focused towards a temperature forecasting application. Forecasting metrological parameters have a profound influence on crop growth, development and yields of agriculture. In response to this fact, an application is developed for 10 days ahead maximum and minimum temperatures forecasting using a type of recurrent neural network.

IoT in Smart Cities: A Survey of Technologies, Practices and Challenges

“…The proliferation of sensing systems in agricultural fields has also provided an avenue for data driven decision making and planning for farmers. This involves predicting various physical parameters which can affect crop growth like solar radiance [95] and temperature, humidity, windspeed [96][97][98][99][100] to help in decision making in terms of plant care but also classification systems for recommending crops to be sown [101,102]. It is important to note that all of these implementations are cloud based.…”

A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming

“…Scientific modelling and machine learning are examples of tools employed for forecasting. Different machine learning models have been employed, such as the regression model, Artificial Neural Networks for forecasting maximum and minimum temperatures at field level [52]; forecasting soil moisture or plant disease detection [48]; for estimating phosphorus level in the soil [53], etc.…”

Enhancing Coffee Supply Chain towards Sustainable Growth with Big Data and Modern Agricultural Technologies

“…Then, the data will be transferred over a network without requiring human-to-human or human-to-computer interaction. For example, Aliev et al [97] studied the application of smart agriculture by using IoT for measuring the temperature, humidity, and soil moisture of plants. Kulalvaimozhi et al [98] used an image processing technique to greatly improve the productivity of agriculture to increase output to meet demand.…”