Fatma Karray, Wassim M. Jmal, Mohamed Abid, Douha Houssaini, Abdulfattah M. Obeid, Syed Manzoor Qasim, Mohammed S. BenSaleh
Architecture of Wireless Sensor Nodes for Water Monitoring Applications: From Microcontroller-based System to SoC Solutions

A significant amount of research and development work has been initiated by several research groups in the recent years to tackle the issue of water monitoring. Wireless sensor network (WSN) is predominantly used for water monitoring application. Depending on the application constraints and performance required, different implementations are considered for the development of wireless sensor nodes for water monitoring applications. Some are based on microcontroller, digital signal processor (DSP), application-specific integrated circuit (ASIC), field programmable gate array (FPGA), system-on-chip (SoC), programmable system-on-chip (PSoC) or a combination of these technologies. This paper presents a survey of state-of-the-art research on sensor node technologies used for water monitoring which includes pipeline monitoring, fresh water monitoring for quality and composition. The relative strengths and weaknesses of microcontroller, DSP, ASIC and FPGA-based wireless sensor nodes for water monitoring applications are presented. Finally, a fully-integrated energy aware SoC solution using reconfigurable hardware is proposed to achieve optimal results.

T. J. Schröder, Ch. Schöberlein, Ch. Schmidt, T. Keutel, O. Kanoun
Mechanical energy converter study for lotic water sensor applications

Wireless sensor systems can help to improve or to expand instrumentation for environmental monitoring systems. A mechanical converter solution will be proposed to convert energy using the Kármán vortex street within lotic water. Within the system design process the focus of this contribution will be in the investigation of the mechanical coupling of turbulences and a mechanical energy converter.

Sabrine Khriji, Dhouha El Houssaini, Christian Viehweger, Olfa Kanoun
A Wireless Sensor Network for Automated Irrigation Systems

The Wireless Sensors Networks (WSN) technology has spread rapidly into different fields and sectors, agriculture is one of them. WSNs for agriculture are used for their cost effectiveness to improve the productivity, profitability and sustainability of the whole farming system. This work focus on the design and implementation of an intelligent, low cost and fully automated irrigation system which will be able to provide full time monitoring. The system is composed of different types of nodes. Each node consists of a TelosB mote and adequate sensors and actuators. In addition, a gateway unit handles sensor information, triggers actuators, and transmits data to a java or web application. To maximize the lifetime of a mote the system was powered by an Energy Harvesting Module using a solar panel.

P. Vergallo, R. Janca, A. Lay-Ekuakille, R. Cmejla, P. Krsek
SOURCE LOCALIZATION OF EPILEPTIC ACTIVITY FROM INTRACRANIAL EEG BY DIRECTION OF ARRIVAL ESTIMATION METHOD

Brain activity source localization is an important issue related to origins of neurological epilepsy disorders which reveal oneself by specific EEG activity. Epilepto-surgery treatment is based on complete removing or disconnecting of epilepsy bearing which is responsible for seizure. However precise localization of epileptogenic tissue partly depends on an accurate localization sources of seizure activity or/and inter-ictal specific activity. In this work the DOA (Direction of Arrival) estimation method Multiple Signal Classification (MUSIC) is used to locate distinct sources of specific epileptic activity from intracranial EEG. It is a subspace-based method which allows distinguishing more sources if they are not very close to each other and the Signal to Noise Ratio (SNR) is not low. Due to the fact that the number of active brain activity sources is usually unknown the estimation of DOAs is difficult as well as the MUSIC. It does not allow in some case to achieve an accurate result. We try to overcome these limits by normalizing the MUSIC spectrum with an estimated noise spatial spectrum which does not require the a priori knowledge of the number of active sources.
The preliminary results show that used DOA Estimation method is able to identify distinct sources of specific activity as inter-ictal epileptiform discharges in intracranial EEG. We conclude, the method could be useful for revealing the epileptogenic zone boundaries.

Rosario Morello, Claudio De Capua, Gianluca Lipari, Maria Grazia Belvedere
A SMARTPHONE-BASED ASSESSMENT TOOL TO EVALUATE PARKINSON’S DISEASE SEVERITY

In this paper, an assessment tool based on smartphone to evaluate disease severity in patients with Parkinson’s disease is proposed. Parkinson’s disease is a pathology widely spread in middle aged and aged individuals of any sex. It is a debilitating and degenerative disorder affecting the central nervous system. Distinctive symptoms are movement-related such as rigidity, slowness of movement and shaking. Further symptoms could be even cause of behavioural problems such as dementia. Today, the disease severity assessment is performed by means of simple visual examination or by using specific medical instrumentation. The Unified Parkinson’s Disease Rating Scale is used to define the progress status of disease. However, this ordinal scale allows physician to evaluate only qualitatively the pathology severity. Moreover, this evaluation requires expert medical staff, and sometimes, even the admission of patient to hospital is needed. For these reasons, the authors propose a smartphone app, which is able to record and process involuntary tremors of patient hand. Information, concerning amplitude and frequency of acceleration levels, is compared with patient historical data in order to assess the progress of disease.