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Knowledge of spatial and temporal trends in the environmental exposure to radiofrequency electromagnetic fields (RF-EMF) is a key prerequisite for RF-EMF risk assessment studies attempting to establish a link between RF-EMF and potential effects on human health as well as on fauna and flora. In this paper, we determined the validity of RF exposure modelling based on inner-area kriging interpolation of measurements on the surrounding streets. The results vary depending on area size and shape and structural factors; a Spearman coefficient of 0.8 and a relative error of less than 3.5 dB are achieved on a data set featuring a closed measurement ring around a decently sized area (1 km 2 , with an average minimum distance of the encircled area to the ring of less than 100 m), containing mainly low, detached buildings. In larger areas, additional inner-area sampling is advised, lowering the average minimum distance between sampled and interpolated locations to 100 m, to achieve the same level of accuracy. [ABSTRACT FROM AUTHOR]

With the rising energy price and the ever-increasing consciousness of environmental friendliness, it is becoming practically helpful for manufacturers to have a clear view on how the energy is consumed at their shop floors, what the corresponding energy cost is, and how to reduce the energy consumption or the energy cost. However, there is currently limited literature investigating the energy cost minimization in manufacturing through production scheduling under volatile energy prices. This paper proposes a generic mixed-integer linear programming model to enable the job scheduling on a single machine for the purpose of minimizing the necessary energy cost without exceeding the due date. The results given by a case study on a surface grinding machine demonstrate this scheduling methodology effectively contributes to the reduction of greenhouse gas emissions during peak time periods by shifting the production load to off-peak periods, and leads to energy-efficient, demand-responsive, and cost-effective manufacturing processes. [ABSTRACT FROM AUTHOR]

Temporal radio frequency (RF) exposure from present and emerging technologies in sensitive microenvironments such as schools and homes is important for evaluations of compliance to international limits. For the first time, temporal 24-hour measurements of all present RF signals, including LTE (Long term Evolution), are performed with accurate spectral narrowband equipment in these environments where children are present. The largest maximal variations are obtained for the cordless telephony (DECT) signals (10.6 dB) and for the WiFi 2.4 GHz signals (12.7 dB), while variations of broadcasting signals and telecommunication signals were much lower namely, 2.9 dB and 3.3 dB, respectively. Thus, indoor sources exhibit the largest variations indoor and are the most critical for practical exposure assessment and comparison with existing guidelines. It is recommended to perform exposure measurements during school days as highest field values were measured then. All field values measured over 24 hour satisfied the ICNIRP reference levels. [ABSTRACT FROM AUTHOR]

Abstract: Background: Concerns of the general public about potential adverse health effects caused by radio-frequency electromagnetic fields (RF-EMFs) led authorities to introduce precautionary exposure limits, which vary considerably between regions. It may be speculated that precautionary limits affect the base station network in a manner that mean population exposure unintentionally increases. Aims: The objectives of this multicentre study were to compare mean exposure levels in outdoor areas across four different European cities and to compare with regulatory RF-EMF exposure levels in the corresponding areas. Methods: We performed measurements in the cities of Amsterdam (the Netherlands, regulatory limits for mobile phone base station frequency bands: 41–61V/m), Basel (Switzerland, 4–6V/m), Ghent (Belgium, 3–4.5V/m) and Brussels (Belgium, 2.9–4.3V/m) using a portable measurement device. Measurements were conducted in three different types of outdoor areas (central and non-central residential areas and downtown), between 2011 and 2012 at 12 different days. On each day, measurements were taken every 4s for approximately 15 to 30min per area. Measurements per urban environment were repeated 12 times during 1year. Results: Arithmetic mean values for mobile phone base station exposure ranged between 0.22V/m (Basel) and 0.41V/m (Amsterdam) in all outdoor areas combined. The 95th percentile for total RF-EMF exposure varied between 0.46V/m (Basel) and 0.82V/m (Amsterdam) and the 99th percentile between 0.81V/m (Basel) and 1.20V/m (Brussels). Conclusions: All exposure levels were far below international reference levels proposed by ICNIRP (International Commission on Non-Ionizing Radiation Protection). Our study did not find indications that lowering the regulatory limit results in higher mobile phone base station exposure levels. [Copyright &y& Elsevier]

Abstract: Wireless Local Area Networks (WLANs) are commonly deployed in various environments. The WLAN data packets are not transmitted continuously but often worst-case exposure of WLAN is assessed, assuming 100% activity and leading to huge overestimations. Actual duty cycles of WLAN are thus of importance for time-averaging of exposure when checking compliance with international guidelines on limiting adverse health effects. In this paper, duty cycles of WLAN using Wi-Fi technology are determined for exposure assessment on large scale at 179 locations for different environments and activities (file transfer, video streaming, audio, surfing on the internet, etc.). The median duty cycle equals 1.4% and the 95th percentile is 10.4% (standard deviation SD = 6.4%). Largest duty cycles are observed in urban and industrial environments. For actual applications, the theoretical upper limit for the WLAN duty cycle is 69.8% and 94.7% for maximum and minimum physical data rate, respectively. For lower data rates, higher duty cycles will occur. Although counterintuitive at first sight, poor WLAN connections result in higher possible exposures. File transfer at maximum data rate results in median duty cycles of 47.6% (SD = 16%), while it results in median values of 91.5% (SD = 18%) at minimum data rate. Surfing and audio streaming are less intensively using the wireless medium and therefore have median duty cycles lower than 3.2% (SD = 0.5–7.5%). For a specific example, overestimations up to a factor 8 for electric fields occur, when considering 100% activity compared to realistic duty cycles. [Copyright &y& Elsevier]

Abstract: In this letter, measurements of the industrial power delay profile are presented. Measurements are performed through frequency-domain channel sounding in the range from 800MHz to 4GHz and by using the virtual antenna array method. Received power as a function of delay clearly exhibits clustering and is for this reason fitted to the well-known Saleh–Valenzuela model. With this, new statistical modifications to the rates of power decay in the Saleh–Valenzuela model are presented. It is found that the model''s parameters do not seem to differ significantly between LOS and NLOS. Small-scale fading is Rayleigh distributed except for the first arriving delay tap, for which a Nakagami- distribution provides a better fit. [Copyright &y& Elsevier]

Generally, industry includes various sectors like manufacturing, energy, materials & mining, and transportation. Industry consumes about one half of the world's total delivered energy, and manufacturing is one of the energy-intensive industrial sectors. With the rising energy price, the energy cost is becoming a controllable expenditure in manufacturing. In this paper, a generic method has been proposed to minimize the energy cost and improve the energy efficiency of manufacturing unit processes. Finite state machines have been used to build the transitional state-based energy model of a single machine. A mixed-integer linear programming mathematical model has been formulated for energy-cost-aware job order scheduling on a single machine. A generic algorithm has been implemented to search for an energy-cost-effective schedule at volatile energy prices with the constraint of due dates. As a result, plant managers can have an energy-cost-effective job order schedule which is associated with machine energy states along time, and can also get time-indexed energy simulation of the schedule. In comparison to most of the static scheduling approaches, stochasticity has been further handled through a cyclic interaction between the scheduler and the energy model, which facilitates to investigate how stochasticity on a shop floor affects the performance of energy-cost-aware scheduling. Empirical data have been used in the case study, including the power measured from a grinding machine, and the real-time pricing and time-of-use pricing tariffs. The proposed method has been demonstrated to be both energy-efficient and energy-cost-efficient even at the presence of stochasticity. As a joint effort of energy efficiency and demand response within demand side management, this method shows its effectiveness for contributing to the reduction of greenhouse gas emissions during peak periods, and for leading to energy-efficient, demand-responsive, and cost-effective manufacturing processes. [ABSTRACT FROM AUTHOR]

Abstract Energy-aware production scheduling is a promising way to adapt the factories' energy consumption behavior to the volatile electricity prices in the demand response initiative of smart grids. However, it may not be economical by simply scheduling production loads to the periods with lower electricity prices, as these periods often have higher labor wage, e.g., nights and weekends. Based on this gap, this paper proposes a many-objective integrated energy- and labor-aware flexible job shop scheduling model. Many objectives refer to the number of optimization objectives surpasses three (i.e., five objectives: makespan, total energy cost, total labor cost, maximal workload, and total workload), whereas the existing energy-aware production scheduling research is limited within three objectives. To enable energy awareness in the conventional production scheduling algorithms, a state-based shop floor wide energy model is proposed. To enable labor awareness, the number and type of human workers are matched to the scheduled production loads, with varying labor wage over shifts. As one of the most complex shop floor configurations, the partial flexible job shop further considers job recirculation and operation sequence-dependent machine setup times. The recently-proposed nondominated sorting genetic algorithm-III (NSGA-III) is tailored for this many-objective optimization problem (MaOP), including scheduling solution encoding and decoding, crossover, mutation, and solution evaluation using the energy- and labor-aware discrete-event simulation framework. Through numerical experiments under real-time pricing (RTP) and time-of-use pricing (ToUP), insights are statistically obtained on the relation among these five production objectives; the effectiveness and efficiency of NSGA-III in solving a MaOP are also demonstrated. This proposed scheduling method can be used to automated and enhance the decision making of factory managers in jointly allocating machine, human worker, and energy resources on the shop floor, such that the production cost is minimized even under time-varying electricity and labor prices. Highlights • Method to integrate both energy and labor awareness in conventional production scheduling models. • The most complex shop floor configuration is considered in this novel production scheduling model. • Many-objective optimization is investigated for the first time in the production scheduling domain. • The recently-proposed NSGA-III is tailored to solve this novel scheduling model. [ABSTRACT FROM AUTHOR]

Highlights • Simple decision-tree (DT) algorithm to classify feeding and ruminating behaviours. • The DT performs similar to support vector machine and a RumiWatch noseband. • The use of a simple DT would help implementing the algorithm on the on-cow sensor. • It would enable online measurements of the ingestive-related cow behaviours. Abstract A new simple decision-tree (DT) algorithm was developed using the data from a neck-mounted accelerometer for real-time classification of feeding and ruminating behaviours of dairy cows. The performance of the DT was compared to that of a support vector machine (SVM) algorithm and a RumiWatch noseband sensor and the effect of decreasing the sampling rate of the accelerometer on the classification accuracy of the developed algorithms was investigated. Ten multiparous dairy cows were used in this study. Each cow was fitted with a RumiWatch halter and an accelerometer attached to the cow's collar with both sensors programmed to log data at 10 Hz. Direct observations of the cows' behaviours were used as reference (baseline data). Results indicate that the two sensors have similar classification performances for the considered behavioural categories (i.e., feeding, ruminating, other activity), with an overall accuracy of 93% for the accelerometer with SVM, 90% for the accelerometer with DT, and 91% for the Rumiwatch sensor. The difference between the predicted and the observed ruminating time (in min/h) was less than 1 min. h (1.5% of the observed time) for the SVM and less than 2 min. h (2.8%) for both DT and the RumiWatch. Similarly, the difference in feeding time was 1.3 min. h (2.1%) for the SVM compared to 2.5 min. h (4.3%) and 2.4 min. h (4.1%) for both RumiWatch and DT, respectively. These preliminary findings illustrate the potential of the collar-mounted accelerometer to classify feeding and ruminating behaviours with accuracy measures comparable to the Rumiwatch noseband sensor. [ABSTRACT FROM AUTHOR]

With the penetration of Internet of things in manufacturing industry, it is an unavoidable issue to maintain robust wireless connections among machines and human workers in harsh industrial environments. However, the existing wireless planning tools focus on office environments, which are less harsh than industrial environments regarding shadowing effects of diverse obstacles. To fill this gap, this paper proposes an over-dimensioning (OD) model, which automates the decision making on deploying a robust industrial wireless local area network (IWLAN). This model creates two full coverage layers while minimizing the deployment cost, and guaranteeing a minimal separation distance between two access points (APs) to prevent APs that cover the same region from being simultaneously shadowed by an obstacle. Moreover, an empirical one-slope path loss model, which considers three-dimensional obstacle shadowing effects, is proposed for simple yet precise coverage calculation. To solve this OD model even at a large size, an efficient genetic algorithm based over-dimensioning (GAOD) algorithm is designed. Genetic operators, parallelism, and speedup measures are tailored to enable large-scale optimization. A greedy heuristic based over-dimensioning (GHOD) algorithm is further proposed, as a state-of-the-art heuristic benchmark algorithm. In small- and large-size OD problems based on industrial data, the GAOD was demonstrated to be 20%–25% more economical than benchmark algorithms for OD in the same environment. The effectiveness of GAOD was further experimentally validated with a real deployment system. Though this paper focuses on an IWLAN, the proposed GAOD can serve as a decision making tool for deploying other types of robust industrial wireless networks in terms of coverage, such as wireless sensor networks and radio-frequency identification (RFID) networks. [ABSTRACT FROM AUTHOR]

With the penetration of smart grid into factories, energy-efficient production scheduling has emerged as a promising method for industrial demand response. It shifts flexible production loads to lower-priced periods to reduce energy cost for the same production task. However, the existing methods only focus on integrating energy awareness to conventional production scheduling models. They ignore the labor cost which is shift-based and follows an opposite trend of energy cost. For instance, the energy cost is lower during nights while the labor cost is higher. Therefore, this paper proposes a method for energy-efficient and labor-aware production scheduling at the unit process level. This integrated scheduling model is mathematically formulated. Besides the state-based energy model and genetic algorithm-based optimization, a continuous-time shift accumulation heuristic is proposed to synchronize power states and labor shifts. In a case study of a Belgian plastic bottle manufacturer, a set of empirical sensitivity analyses were performed to investigate the impact of energy and labor awareness, as well as the production-related factors that influence the economic performance of a schedule. Furthermore, the demonstration was performed in 9 large-scale test instances, which encompass the cases where energy cost is minor, moderate, and major compared to the joint energy and labor cost. The results have proven that the ignorance of labor in existing energy-efficient production scheduling studies increases the joint energy and labor cost, although the energy cost can be minimized. To achieve effective production cost reduction, energy and labor awareness are recommended to be jointly considered in production scheduling. [ABSTRACT FROM AUTHOR]

The aims of this study were to: i) measure personal exposure in the Global System for Mobile communications (GSM) 900 MHz downlink (DL) frequency band with two systems of exposimeters, a personal distributed exposimeter (PDE) and a pair of ExpoM-RFs, ii) compare the GSM 900 MHz DL exposures across various microenvironments in Australia and Belgium, and iii) evaluate the correlation between the PDE and ExpoM-RFs measurements. Personal exposure data were collected using the PDE and two ExpoM-RFs simultaneously across 34 microenvironments (17 each in Australia and Belgium) located in urban, suburban and rural areas. Summary statistics of the electric field strengths (V/m) were computed and compared across similar microenvironments in Australia and Belgium. The personal exposures across urban microenvironments were higher than those in the rural or suburban microenvironments. Likewise, the exposure levels across the outdoor were higher than those for indoor microenvironments. The five highest median exposure levels were: city centre (0.248 V/m), bus (0.124 V/m), railway station (0.105 V/m), mountain/forest (rural) (0.057 V/m), and train (0.055 V/m) [Australia]; and bicycle (urban) (0.238 V/m), tram station (0.238 V/m), city centre (0.156 V/m), residential outdoor (urban) (0.139 V/m) and park (0.124 V/m) [Belgium]. Exposures in the GSM 900 MHz frequency band across most of the microenvironments in Australia were significantly lower than the exposures across the microenvironments in Belgium. Overall correlations between the PDE and the ExpoM-RFs measurements were high. The measured exposure levels were far below the general public reference levels recommended in the guidelines of the ICNIRP and the ARPANSA. [ABSTRACT FROM AUTHOR]

Abstract: Personal radio frequency electromagnetic field (RF-EMF) exposure, or exposimetry, is gaining importance in the bioelectromagnetics community but only limited data on personal exposure is available in indoor areas, namely schools, crèches, homes, and offices. Most studies are focused on adult exposure, whereas indoor microenvironments, where children are exposed, are usually not considered. A method to assess spatial and temporal indoor exposure of children and adults is proposed without involving the subjects themselves. Moreover, maximal possible daily exposure is estimated by combining instantaneous spatial and temporal exposure. In Belgium and Greece, the exposure is measured at 153 positions spread over 55 indoor microenvironments with spectral equipment. In addition, personal exposimeters (measuring EMFs of people during their daily activities) captured the temporal exposure variations during several days up to one week at 98 positions. The data were analyzed using the robust regression on order statistics (ROS) method to account for data below the detection limit. All instantaneous and maximal exposures satisfied international exposure limits and were of the same order of magnitude in Greece and Belgium. Mobile telecommunications and radio broadcasting (FM) were most present. In Belgium, digital cordless phone (DECT) exposure was present for at least 75% in the indoor microenvironments except for schools. Temporal variations of the exposure were mainly due to variations of mobile telecommunication signals. The exposure was higher during daytime than at night due to the increased voice and data traffic on the networks. Total exposure varied the most in Belgian crèches (39.3%) and Greek homes (58.2%). [Copyright &y& Elsevier]

• Personal exposimeters are often used for RF-EMF measurements, but have shortcomings. • We developed a novel on-body calibrated device with distributed sensors (BWDM). • BWDM is designed to minimize body shielding and to use frequency specific antennas. • We measured RF-EMF exposures in parallel with three types of devices. • Exposimeters provide slightly lower exposures but rank averaged exposures accurately. Exposure to radiofrequency electromagnetic fields (RF-EMF) is often measured with personal exposimeters, but the accuracy of measurements can be hampered as carrying the devices on-body may result in body shielding. Further, the compact design may compromise the frequency selectivity of the sensor. The aim of this study was to compare measurements obtained using a multi-band body-worn distributed-exposimeter (BWDM) with two commercially available personal exposimeters (ExpoM-RF and EmeSpy 200) under real-life conditions. The BWDM measured power density in 10 frequency bands (800, 900, 1800, 2100, 2600 MHz, DECT 1900 MHz, WiFi 2.4 GHz; with separate uplink/downlink bands for 900, 1800 and 2100 MHz); using 20 separate antennas integrated in a vest and placed on diametrically opposite locations on the body, to minimize body-shielding. RF-EMF exposure data were collected from several microenvironments (e.g. shopping areas, train stations, outdoor rural/ urban residential environments, etc.) by walking around pre-defined areas/routes in Belgium, Spain, France, the Netherlands and Switzerland. Measurements were taken every 1–4 s with the BWDM in parallel with an ExpoM-RF and an EmeSpy 200 exposimeter. We calculated medians and interquartile ranges (IQRs) and compared difference, ratios and correlations of geometric mean RF-EMF exposure levels per microenvironment as measured with the exposimeters and the BWDM. Across 267 microenvironments, medians and IQR of total BWDM measured RF-EMF exposure was 0.13 (0.05–0.33) mW/m2. Difference: IQR of exposimeters minus BWDM exposure levels was −0.011 (−0.049 to 0.0095) mW/m2 for the ExpoM-RF and −0.056 (−0.14 to −0.017) for the EmeSpy 200; ratios (exposimeter/BWDM) of total exposure had an IQR of 0.79 (0.55–1.1) for the ExpoM-RF and 0.29 (0.22–0.38) for the EmeSpy 200. Spearman correlations were 0.93 for the ExpoM-RF vs the BWDM and 0.96 for the EmeSpy 200 vs the BWDM. Results indicate that exposimeters worn on-body provide somewhat lower total RF-EMF exposure as compared to measurements conducted with the BWDM, in line with effects from body shielding. Ranking of exposure levels of microenvironments showed high correspondence between the different device types. Our results are informative for the interpretation of existing epidemiological research results. [ABSTRACT FROM AUTHOR]

Objective: To investigate the association between estimated whole-brain radiofrequency electromagnetic fields (RF-EMF) dose, using an improved integrated RF-EMF exposure model, and cognitive function in preadolescents and adolescents.Methods: Cross-sectional analysis in preadolescents aged 9-11 years and adolescents aged 17-18 years from the Dutch Amsterdam Born Children and their Development Study (n = 1664 preadolescents) and the Spanish INfancia y Medio Ambiente Project (n = 1288 preadolescents and n = 261 adolescents), two population-based birth cohort studies. Overall whole-brain RF-EMF doses (mJ/kg/day) were estimated for several RF-EMF sources together including mobile and Digital Enhanced Cordless Telecommunications phone calls (named phone calls), other mobile phone uses than calling, tablet use, laptop use (named screen activities), and far-field sources. We also estimated whole-brain RF-EMF doses in these three groups separately (i.e. phone calls, screen activities, and far-field) that lead to different patterns of RF-EMF exposure. We assessed non-verbal intelligence in the Dutch and Spanish preadolescents, information processing speed, attentional function, and cognitive flexibility in the Spanish preadolescents, and working memory and semantic fluency in the Spanish preadolescents and adolescents using validated neurocognitive tests.Results: Estimated overall whole-brain RF-EMF dose was 90.1 mJ/kg/day (interquartile range (IQR) 42.7; 164.0) in the Dutch and Spanish preadolescents and 105.1 mJ/kg/day (IQR 51.0; 295.7) in the Spanish adolescents. Higher overall estimated whole-brain RF-EMF doses from all RF-EMF sources together and from phone calls were associated with lower non-verbal intelligence score in the Dutch and Spanish preadolescents (-0.10 points, 95% CI -0.19; -0.02 per 100 mJ/kg/day increase in each exposure). However, none of the whole-brain RF-EMF doses was related to any other cognitive function outcome in the Spanish preadolescents or adolescents.Conclusions: Our results suggest that higher brain exposure to RF-EMF is related to lower non-verbal intelligence but not to other cognitive function outcomes. Given the cross-sectional nature of the study, the small effect sizes, and the unknown biological mechanisms, we cannot discard that our resultsare due to chance finding or reverse causality. Longitudinal studies on RF-EMF brain exposure and cognitive function are needed. [ABSTRACT FROM AUTHOR]

• We estimated overall and source-specific RF-EMF doses to the brain. • Estimated overall whole-brain RF-EMF dose was 84.3 mJ/kg/day. • Overall whole-brain or lobe-specific RF-EMF doses were not related to brain volumes. • Whole-brain RF-EMF dose from mobile communication devices for screen activities while wirelessly connected to the internet was associated with smaller caudate volume. • We cannot discard residual confounding, chance finding, or reverse causality. To assess the association between estimated whole-brain and lobe-specific radiofrequency electromagnetic fields (RF-EMF) doses, using an improved integrated RF-EMF exposure model, and brain volumes in preadolescents at 9–12 years old. Cross-sectional analysis in preadolescents aged 9–12 years from the Generation R Study, a population-based birth cohort set up in Rotterdam, The Netherlands (n = 2592). An integrated exposure model was used to estimate whole-brain and lobe-specific RF-EMF doses (mJ/kg/day) from different RF-EMF sources including mobile and Digital Enhanced Cordless Telecommunications (DECT) phone calls, other mobile phone uses than calling, tablet use, laptop use, and far-field sources. Whole-brain and lobe-specific RF-EMF doses were estimated for all RF-EMF sources together (i.e. overall) and for three groups of RF-EMF sources that lead to a different pattern of RF-EMF exposure. Information on brain volumes was extracted from magnetic resonance imaging scans. Estimated overall whole-brain RF-EMF dose was 84.3 mJ/kg/day. The highest overall lobe-specific dose was estimated in the temporal lobe (307.1 mJ/kg/day). Whole-brain and lobe-specific RF-EMF doses from all RF-EMF sources together, from mobile and DECT phone calls, and from far-field sources were not associated with global, cortical, or subcortical brain volumes. However, a higher whole-brain RF-EMF dose from mobile phone use for internet browsing, e-mailing, and text messaging, tablet use, and laptop use while wirelessly connected to the internet was associated with a smaller caudate volume. Our results suggest that estimated whole-brain and lobe-specific RF-EMF doses were not related to brain volumes in preadolescents at 9–12 years old. Screen activities with mobile communication devices while wirelessly connected to the internet lead to low RF-EMF dose to the brain and our observed association may thus rather reflect effects of social or individual factors related to these specific uses of mobile communication devices. However, we cannot discard residual confounding, chance finding, or reverse causality. Further studies on mobile communication devices and their potential negative associations with brain development are warranted, regardless whether associations are due to RF-EMF exposure or to other factors related to their use. [ABSTRACT FROM AUTHOR]

This paper presents a simulation study of the impact of Light Emitting Diode (LED) output power uncertainty on the accuracy of Received Signal Strength (RSS)-based two-dimensional (2D) and three-dimensional (3D) Visible Light Positioning (VLP). The actual emitted power of a LED is never exactly equal to the value that is tabulated in the datasheet, with possible variations (or tolerances) up to 20%. Since RSS-based VLP builds on converting estimated channel attenuations to distances and locations, this uncertainty will impact VLP accuracy in real-life setups. For 2D, a typical configuration with four LEDs is assumed here, and a Monte-Carlo simulation is executed to investigate the distribution of the resulting positioning errors for four tolerance values at seven locations. It is shown that median errors are the highest just below the LEDs, when using a traditional Least-Squares minimization metric. When tolerance values on the LED power increase from 5% to 20%, median errors vary from at most 2 cm to at most 10 cm. Maximal errors can be as high as 17 cm just below the LED, already for tolerance values of only 5%, and increase up to 40 cm for tolerance values of 20%. An alternative cost metric using normalized Least-Squares minimization makes the errors spatially more homogeneously distributed and reduces them by 35%. For a 3D case, median errors of around 5 cm for a tolerance value of 5% increase to as much as 22 cm for a tolerance value of 20%. As the receiver heights increase, positioning errors decrease significantly. [ABSTRACT FROM AUTHOR]