Since July 1, 2016 the Directive 2013/35 / EU on the protection of human health against the effects of non-ionizing electromagnetic radiation, acquires the force of law. As regards low frequency exposure assessment, it requires a clearly different treatment of electric and respectively magnetic fields, from all the important perspectives: sensors, measuring techniques, biological effects and methods of protection. In this paper we propose a methodology accessible (both for SME employers and for a regulatory and/or control authority at the beginning of its activity) for the characterization of a workspace, in terms of exposure to low-frequency electric fields. After a review of the main sources of such fields, we have done a comparative summary of the exposure levels considered acceptable by the leading global institutions involved in this domain (ICNIRP, IEEE, WHO). We have presented our artisanal electric field sensor, the low-frequency handheld spectrum analyzer, spatial and temporal averaging techniques, methods for summarizing the fields and harmonics of different frequencies and specific uncertainties that should be considered. Finally we have presented a case study on the assessment of exposure to low frequency electric fields produced in a laboratory room where a network of 16 computers was working.

The importance of research on new technologies that could be employed in care services for elderly and disabled persons is highlighted. Advantages of radar sensors, when applied for noninvasive monitoring of such persons in their home environment, are indicated. Methods for estimation of the instantaneous velocity and the mean walking velocity (including automatic detection of time intervals when the person is in motion), on the basis of the measurement data from radar sensors and accelerometers, are described. A novel methodology for evaluation of the estimation uncertainty of the person’s average walking velocity, in an impulseradar-based system for monitoring of movements, is presented. The results of a series of real-world experiments, with a person moving at different predefined velocities, are shown. They are indicating that the accuracy of radar-data-based detection of the person’s motion and estimation of person’s walking velocity may be sufficient for some healthcare applications.

The aim of the paper is to estimate thermal properties (thermal conductivity and thermal diffusivity) of the concrete wall with unknown insulation. Short theoretical background of diffusive heat transfer and numerical solution of unsteady onedimensional heat conduction equation is presented first. System of discretized equations is solved using MATLAB. Boundary conditions (i.e. temperatures on edges of the wall) required for solving parabolic partial differential equation are obtained from experimental measurements on the wall. One heat flux sensor and one temperature sensor is mounted on both sides of the wall. Temperature inside room is maintained on approximately constant value by air conditioner while outdoor temperature is varying through the day. Measured signals are collected using NI cDAQ and then analyzed, processed and displayed using LabVIEW. Measured heat flux and numerically calculated heat flux from room to wall are then compared and initially chosen thermal conductivity and thermal diffusivity of the wall are iteratively adjusted until difference between measured and simulated heat flux is minimized.

Modern power applications are demanding for broadband current sensors. Hall sensors are a good solution from a general standpoint, but practical implementations are limited to a few hundred kHz. In fact, many parasitic dynamic effects perturb the time response of the Hall sensor, making difficult to experimentally assess the fundamental frequency limit and achieve it in the applications. This paper presents an equivalent electrical model that helps to design a test aimed at experimentally estimating the intrinsic time response of the sensor. According this test, the paper demonstrates that Hall sensors have an upper bandwidth limit defined by the overall capacitive load. Moreover, some of the parasitic dynamic effects, which degrade the time response in real operation, are identified and investigated.

Drought is one of the most common natural events having a great negative impact on agriculture being associated with a deficit of water resources over large geographical areas. Drought severity is conventionally assessed by various drought indices, which depend on different types of data. Among them, the Reconnaissance Drought Index (RDI) exhibits significant advantages over the other indices in the calculation of the drought severity by using, simultaneously, the precipitation and the potential evapotranspiration cumulated on a reference time scale processing monthly, seasonal or annual data. The main objective of the study was to assess the drought severity in a southern Italy area (Calabria region) by using the RDI and to map its spatial distribution and uncertainty. Calculating RDI requires the availability of precipitation and temperature data covering the whole study area. Precipitation and temperature data can be treated as random variables and analyzed by geostatistical methods. Particularly, to take into account the errors propagation in computing RDI, the input variables (precipitation and temperature data) were simulated using a geostatistical simulation approach. A set of 500 alternative stochastic images of the variables were generated and the expected value and standard deviation for RDI values were mapped.