(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 9, No. 4, 2018 421 | Page www.ijacsa.thesai.org Internet of Plants Application for Smart Agriculture Khurshid Aliev Department of Management and Production Engineering Politecnico Di Torino Torino, Italy. Mohammad Moazzam Jawaid, Sanam Narejo Department of Computer Systems Engineering Mehran University Jamshoro, Pakistan Eros Pasero Department of Electronics and Telecommunication Politecnico Di Torino Torino, Italy. Alim Pulatov Head of EcoGIS centre Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan 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. Keywords—Internet of Things; wireless sensor networks; smart agriculture; smartphone applications; artificial neural network; nonlinear autoregressive model; temperature forecasting I. INTRODUCTION Agriculture is a cultivation of products to feed the population. For centuries, it has remained as a key development factor for human civilization. Moreover, today the demand for efficient agriculture products is increasing [1]. In order to improve agriculture processes, we can acquire field data with sensors, make data analytics, perform analysis and take appropriate decisions and actions. Collecting big data from the field gives us a clearer understanding of product variability and quality of products [2]. In agriculture, physical parameters such as temperature, relative humidity and soil moisture are important [3]. There are several applications and well established measuring instruments to collect these data [4]. In addition, sensors to measure soil properties [5], detect and monitor foliar disease [1] or fertilizer management [6] already exist. Data acquisition systems in agriculture need to cover large areas, collect representative samples and exchange measured information and control commands. In precision agriculture, one of the vital problems is how to distribute sensors and to establish reliable data communications. A robust and reliable data acquisition system enables synchronizing, exchange and storing of measured data. This kind of system is required to efficiently evaluate sensor signals and allow real-time or a- posteriori analysis of the behaviour of single parameters and their mutual impact [7]. Internet of Things (IoT) is receiving a great attention due to its potential strength and ability to be integrated into any complex system. It is becoming a great tool to acquire data from particular environment to the cloud. One of the use case fields of IoT is smart agriculture. However, there are some issues on developing low cost and power efficient WSN using advanced radio technologies for short and long-range applications. To satisfy the need for population, farmers and agriculture companies are turning to the Internet of Things (IoT). The IoT is pushing the future of farming to the next level. Smart agriculture is becoming more commonplace among farmers, and high tech farming is quickly becoming the standard thanks to the agricultural sensors. WSN are playing important role in IoT technologies since it has been discovered. WSN systems are a strong and effective tool to distribute data among sensor nodes. The use of IoT applications and WSN (Wireless Sensor Networks) in the agriculture domain as proposed by other authors are discussed as follows. In [8], the authors have identified the issues related to reliability, autonomy, cost and accessibility to the application domain. The authors of [9] showed farm management system and its architecture is based on Internet of Things features. This architecture gives easy access to acquired data and advice. The authors of [10] have offered the use cases of Cloud Computing in the agriculture area. Moreover, they further describe it in the context of service providers and supply chain for cost-effective services for farmers. In [11], authors have illustrated the controlled architecture of smart agriculture based on IoT and Cloud Computing. Another issue arose with Wireless Sensor Networks (WSN) which must be connected to all sensor nodes in a smart way. The authors of [12] proposed a WSN for precision agriculture where a real-