Constraints over Greenhouse Detection using Wireless Sensor Networks
Keywords:
Wireless sensor network (WSN), greenhouse, environment control, CO2 monitoring, distributed clusteringAbstract
Due to uneven natural distribution of rain water it is very crucial for farmers to monitor and control the equal distribution of water to all crops in the whole farm or as per the requirement of the crop. There is no ideal irrigation method available which may be suitable for all weather conditions, soil structure and variety of crops cultures. Green house technology may be the best solution for this solution. All the parameters of greenhouse require a detailed analysis in order to choose the correct method. It is observed that farmers have to bear huge financial loss because of wrong prediction of weather and incorrect irrigation method to crops. In this contest with the evolution in wireless sensor technologies and miniaturized sensor devices, it is possible to uses them for automatic environment monitoring and controlling the parameters of greenhouse, for Precision Agriculture (PA) application. Now a days WSN is mainly focused on civilian applications such as environment monitoring, object tracking and bio-medical applications. They carry out collaborative activities due to limited resources, such as battery, processor and scarce memory. Nowadays, the applications of WSNs are several and diverse, and the applications in agriculture are still budding. One appealing WSN application is in environmental monitoring and greenhouses, where the plant conditions such as climate and soil does not depend on natural agents. To manage and monitor the environmental factors, sensors and actuators are critical. Under these circumstances, WSN should be used to make a distributed assessment, spreading sensors all over the greenhouse by means of distributed clustering. This paper reveals some grave issues when a wireless sensor network is exposed to real world environment to monitor and manage parameters like temperature, humidity, smoke, CO2, light and greenhouse gases and how distributed clustering mechanisms can be integrated within this monitoring process.
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