Reference [5] presents the design of a new wireless sensor node referred to as GAIA Soil-Mote for precision horticulture applications which use precision agricultural instruments based on the SDI-12 standard developed for intelligent sensory instruments to monitor environmental data. The GAIA Soil-Mote mote is built around a communication infrastructure that uses the IEEE 802.15.4 standard while its software implementation is based on TinyOS [7]. Using a two-phase methodology including (1) laboratory validation of the proposed hardware and software solution in terms of power consumption and autonomy and (2) implementation to monitor broccoli crop in Campo de Cartagena in south-east Spain, the sensor node was validated under real operating conditions which revealed a large potential market in the farming sector, especially for the development of precision agriculture applications.

The SquidBee [8] motes used in our experimentation also rely on the 802.15.4 standard for communication but use a different operating system. Reference [6] reveals the need for high temperature sensors capable of operating in harsh environments for disaster prevention from structural or system functional failures due to increasing temperatures and building upon the limitations of most of the existing temperature sensors proposes a novel passive wireless temperature sensor, suitable for working in harsh environments for high temperature rotating component monitoring. The proposed prototype sensor calibrated successfully up to 235��C proved the concept of temperature sensing through passive wireless communication.

References [9] and [10] address the issues of energy consumption in wireless sensor networks. In [9], the issue of energy consumption is revisited through a state-of-the art technology review of both fields of energy storage and energy harvesting for sensor nodes Brefeldin_A and energy harvesting is discussed with reference to photovoltaics, temperature gradients, fluid flow, pressure variations and vibration harvesting. A survey on energy consumption presented by [10] provides information pertaining to energy consumption in Rockwell’s WINS node and MEDUSA-II. The survey reveals for example that for WINS, tuning the radio receiver increases the power consumption from 383 mW to 752 mW while MEDUSA-II increases its power from 10 mW to 22 mW.

The same survey also shows that using the transmitter increases the power consumption from 771 mW to 1081 mW for WINS and from 19 mW to 27 mW for MEDUSA-II. This suggest that since the power limitation is such a constraint on WSN, it is appropriate to perform significant amounts of data processing and computation while the receiver is in active state, in order to reduce the amount of radio communication.Several solutions have been proposed by researchers and practitioners to address the WSN engineering issues.