QI2S is a project financed in the frame of the European FP7 funding programme, developing the prototype of a lightweight low-power on-board processing platform that operates with a massively parallel many-core technology based on Ramon Chips ITAR free RC64 architecture. This technology will be able, in the future, of reaching performances of hundreds of GOPS and tens of GFLOPS, although for demonstrational purposes it is now implemented on a downscaled FPGA. The hardware platform is demonstrated for real-time on-board analysis of hyperspectral data. QI2S was developed to ensure parallel computational capabilities and an easily reconfigurable architecture, able to generate on-board products in real-time or near real-time. QI2S is a prototype developed and validated in laboratory with a TRL 4.

This poster shows the work-in-progress results of an effective method for predicting the residual battery energy in WSN nodes including the battery behavior. This method uses a hybrid approach consisting of a deterministic part by counting credit points for any operation of the sensor node and a model-based State-of-Charge (SoC) estimation based on battery voltage and temperature. It is applied for Li-Ion accumulators on modified Tmote Sky motes. For demonstration purposes the method is used for cluster head selection in a cluster-based topology formation algorithm to ensure equal distribution of the cluster head role among the network nodes based on the residual energy.