monitoring and controlling all the activities of drip
irrigation system more efficiently. Irrigation system
controls valves by using automated controller to turn ON
OFF. This allows the farmer to apply the right amount of
water at the right time, regardless of the availability of the
labour to turn valves or motor ON OFF. This reduces runoff
over watering saturated soils avoid irrigating at the
wrong time of the day. It improves crop performances and
help in time saving in all the aspects [5]. The management
of this kind of farms requires data acquisition in each
greenhouse and their transfer to a control unit which is
usually located in a control room, separated from the
production area. At present, the data transfer between the
greenhouses and the control system is mainly provided by
a suitable wired communication system, such as a field
bus. In such contexts, even though the replacement of the
wired system with a fully wireless one can appear very
attractive, a fully wireless system can introduce some
disadvantages. A solution based on a hybrid
wired/wireless network, where Controller Area Network
and ZigBee protocols are used. In particular, in order to
integrate at the Data Link Layer the wireless section with
the wired one, a suitable multi-protocol bridge has been
implemented. Moreover, at the Application Layer, porting
of Smart Distributed System services on ZigBee, called
ZSDS, allows one to access the network resources
independently from the network segment [6]. The some
system highlights the development of temperature and soil
moisture sensor that can be placed on suitable locations on
field for monitoring of temperature and moisture of soil,
the two parameters to which the crops are susceptible. The
sensing system is based on a feedback control mechanism
with a centralized control unit which regulates the flow of
water on to the field in the real time based on the
instantaneous temperature and moisture values [7]. Some
system presents Artificial Neural Network (ANN) based
intelligent control system for effective irrigation
scheduling. The proposed Artificial Neural Network
(ANN) based controller was prototyped using MATLAB.
The input parameters like air temperature, soil moisture,
radiations and humidity are modelled. Then using
appropriate method, ecological conditions,
evapotranspiration and type of crop, the amount of water
needed for irrigation was estimated and then associated
results are simulated [8]