WiFi Field Monitoring for E-Pollution Detection Tatjana Sidekerskienė Robertas Damaševičius Department of Applied Mathematics Department of Software Engineering Kaunas University of Technology Kaunas University of Technology Kaunas, Lithuania Kaunas, Lithuania tatjana.sidekerskiene@ktu.lt robertas.damasevicius@ktu.lt Abstract— The paper presents an outline of the development systems, can penetrate thick concrete block walls. People of WiFi field monitoring maps using the Internet-of-Things (IoT) working in offices or students studying in schools are exposed technology. The negative impacts of signals generated by the to 1600 hours of WiFi radiation during an academic year. This WiFi access points on health and measurement metrics are value is larger than the 1640 hours of cell phone use in the discussed. The experimental system for collecting WiFi signal INTERPHONE study associated with a 40% increase in brain data is presented. Finally, the construction of WiFi signal tumors (glioma) [3]. In 2011, the radio frequencies of EMF strength heatmap is discussed and some preliminary results using were qualified by IARC and WHO as possibly increasing the a combination of real worlds and simulated data are presented. risk of malignant brain tumor [4]. Rats exposed to pulsed digital WiFi frequencies (2.4 GHz) for a long-term (25 Keywords—WiFi; field monitoring, e-health, m-health, s- health, e-pollution. months), had a higher rate of both primary and metastatic cancers [5] though other studies did not confirm these findings [6, 7]. I. INTRODUCTION1 WiFi has been linked to electromagnetic hypersensitivity Recently there has been a significant increase of the or ‘idiopathic environmental intolerance to electromagnetic availability of wireless broadband internet access in public fields’ (IEI-EMF). People suffering from IEI-EMF usually spaces. Providers and points of access take the form of have a diverse range of nonspecific physical symptoms (e.g., municipal WiFi networks, community wireless networks, burning skin, headache, dizziness) that they attribute to their advanced mobile phone networks (e.g. 4G), and WiFi cafes, exposure to the EMF emitted by, e.g., mobile phones, mobile restaurants, bookstores and related spaces. The ubiquitous phone base stations, power lines and WiFi [8]. There is some availability of wireless Internet access encourage greater evidence of potential adverse effects including headaches, participation in public spaces such as cafes [1] as free WiFi increased blood pressure, and disturbances to hotspots attract people. The problem is also important in the electroencephalographic (EEG) activity during sleep [9]. domain of Ambient Assisted Living (AAL) and other similar Several papers have been discussing the effects of domains such as Smart Homes to avoid negative impact of radiofrequency radiation (RFR) [10, 11, 12]. In 2011, the massive use of wireless transceivers for Body Area Networks WHO's International Agency for Research on Cancer (IARC) (BAN), Personal Area Networks (PAN), etc. in terms of daily reclassified RF-EMR as potentially carcinogenic to humans electromagnetic (EM) exposure to radiofrequency [13]. Also the EM radiation has been called as the fourth electromagnetic radiation (RF-EMR), ranging between 0 Hz pollution source besides air, water and noise [14]. and 300 GHz in frequency, as well as interference emission compliance. In this context the Wi-Fi devices generally work However, long-time effects of these electromagnetic fields in close proximity to persons, which can lead to higher risks on human and animal health are still unknown. Several studies related to electromagnetic field (EMF) exposure [2]. conducted on the effects of RFR on human health have provided contradictory and inconsistent findings regarding the Electromagnetic fields (EMF) of all frequencies is one of actual health risks associated with RFR [15-22]. the most fastest growing environmental pollutant. All people are now exposed to varying degrees of EMF, and the levels Summarizing, when considering the health-related risks of are expected continue to increase in future. Wireless access the use of WiFi technology in public spaces there is the need points (APs) and wireless laptops are also often close to to perform modeling of the locations of WiFi access points in humans. WiFi enabled tablets such as iPads or SmartPhones public buildings as well as in private houses to evaluate and are handheld and thus provide more radiation directly into minimize the exposure of people to EM radiation while human body. The exposure in public spaces and buildings can ensuring the quality and signal strength of WiFi connections. be even worse than in homes as hundreds of people are Proposing the computational intelligence methods that allow simultaneously connecting to the internet. to minimize the effects of e-pollution is a growing research stream [23-29]. EMF radiation form industrial grade WiFi systems, which are more than 10 times more powerful as domestic WiFi This paper presents an initial research towards developing such system using Wireless Sensor Network (WSN) and the 1 Copyright © 2016 held by the authors. Internet-of-Things (IoT) technology. 51 II. RELATED WORKS development of wireless technology, including mobile phones, A number of systems were developed to support the Wi-Fi, and various kinds of inter-connected devices making measurement of WiFi fields both in outside environment as up the Internet-of-Things. Biologic material readily interferes well as in buildings. For example, Bell and Jung [30] used with HF-EMF in a way that depends upon its shape, the Netstumbler 0.4.0 for detecting available WLAN service and conductivity and density of the tissue, and the frequency and collecting WiFi signal strength data. Netstumbler observes all amplitude of the EMF leading to an elevation of the tissue APs within the wireless card’s visible range. Spatial and signal temperature and thermal-associated metabolic responses [35]. strength data were integrated after data was collected. Chan et When RF exposures are taken into account, the main al. [31] detect the IEEE 802.11b Wi-Fi signal strength and mechanism to be considered is the ability of RF fields to collect into a database. They also create a fuzzy color map to increase an average temperature through the vibration of visualize the distribution of Wi-Fi signal. StumbVerter [32] is atoms and molecules in the biological tissue. The heat effect a wireless visualization tool that relies on Microsoft’s depends on water content of the biological target material, as MapPoint mapping library. It plots wireless transmitters on a well as on the frequency and intensity of the electromagnetic street map using color to indicate signal strength. However, it (EM) radiation. The characteristic quantity is the Specific lacks signal range mapping and it does not provide imagery Absorption Rate (SAR) [36]. SAR can be calculated as data. Rensburg [33] use of GPS (Global Positioning System) follows [2]: device, PDA and a tool to measure wireless signal characteristics. Rose [34] describe Argos, the urban-scale σ 2 SAR = E WSN designed explicitly to support measurement of ambient ρ WiFi traffic across an entire city. Argos allows urban-scale monitoring of wireless networks. To achieve high spatial here σ = 10.18 m/s is skin conductivity, ρ =1043 kg/m3 coverage, this requires multiple sensor nodes deployed is skin density, and E is the electric field strength. throughout a city that can capture ambient wireless network traffic. Exposure to RF radiation (mainly from mobile phones) has been postulated to trigger a variety of neurological effects, Several large-scale WiFI databases exist, which could be including headaches, changes in sleep pattern, modification in used for researching the harms of exposure to WiFi fields: the neuronal electrical activity, and disturbance in the neurotransmitter release [37]. Increasing evidence indicates • Wigle (http://wigle.net/): a website for collecting that oxidative stress may be involved in the adverse effects in information about the different wireless hotspots the nervous system. Ilhan et al. [38] reported a marked around the world; oxidative damage in brain tissues of rats exposed to 900 MHz • IGiGLE: Irongeek's WiGLE: WiFi Database to signal for GSM (Global System for Mobile communications) Google Earth Client for Wardrive Mapping (SAR of 2 Wkg−1 in the brain) for 7 days. (http://www.irongeek.com/); The SAR values are not directly measurable and depend on • Skyhook (http://www.skyhookwireless.com): a the frequency. Therefore, so-called reference levels have been database containing unique IDs of more than 16 defined that are comparatively easy to measure. For the million wireless routers and their locations. frequency range 0.8–2.8 GHz, the reference levels are approximately 33–62 Vm−1 (general public) and 49–92 Vm−1 (occupational) [39]. Mobile phones are legally limited to a III. CHARACTERISTICS OF WIFI SIGNALS specific absorption rate (SAR) of 2.0 W/kg [40], while most Usually Wi-Fi systems are based on the IEEE Standards have a SAR of ~1.4 W/kg [41]. 802.11b and 802.11g and operate in the 2.4 GHz frequency band. According to the various local legislations and IV. DEVELOPMENT OF WIFI FIELD MONITORING SYSTEM regulations, Wi-Fi devices which are designed for private (domestic) use should emit low power (less than 20 dBm or The system is implemented the following technologies and 100 mW) and should work in a frequency band also used by methods: other communication devices (such as cordless phones). Wi-Fi 1) Internet-of-Things: smart things and devices (e.g. devices based on the IEEE Standard 802.11a operate in the smartphones) that have necessary means to measure WIFI frequency band of 5.8 GHz and are suitable to be used in field intensity. public environment. The IEEE Standard 802.11n works in both frequency bands of 2.4 and 5.8 GHz. Tthe most 2) Web services. Availability of free web services to commonly used technologies are 802.11b and 802.11g (2.4 share data. GHz, maximum output power 100 mW) and the 802.11a (5.8 3) Crowdsourcing. A community based effort using GHz, maximum output power 1 W). contribution of multiple users which High frequency (i.e., frequencies from 300 MHz to 3 GHz) We use a standard three-tiered architecture consisting of: electromagnetic fields are mainly human-produced, nonionizing electromagnetic radiations that do not naturally 1) Data gathering layer: a potentially large number of occur in the environment, excluding the cosmic radiation. HF- devices that gather information about Wi-Fi field strength and EMF are present in the environment because of the active sense it with geodata to the data feeds. 52 2) Data feed layer that publishes gathered data online here: d - distance, f - frequency, K - constant that depends for further use by anyone including any applications beyond on the units used for d and f. If d is measured in kilometers, f Wi-Fi mapping. in MHz, then K=32.44. 3) Data aggregator layer that aggregates and integrates From Eq. (1), we can find out the distance as follows: all data from data feeds and represents it as a map. We used Litepoint IQView equipment to measure WiFi d ( km ) = 10 ( FSPL – 32.44 – 20log10 ( f ) ) / 20 (2) signal strength. A LitePoint IQview 802.11a/b/g WLAN tester was used to sample the ISM band at 66 M/s, centered around 2.412 GHz (WLAN channel 1). The Litepoint IQView device The Fresnel Zone is the area around the visual line-of-sight digitizes the received signal and records the data onto the that radio waves spread out into after they leave the antenna. laptop using UDP transfer connection. The results were You want a clear line of sight to maintain strength, especially processed using Matlab 8.1 (R2013a) to generate heat map of for 2.4GHz wireless systems. This is because 2.4GHz waves signal strength. are absorbed by water, like the water found in trees. The rule of thumb is that 60% of Fresnel Zone must be clear of A computer is connected with the measurement device via obstacles. Typically, 20% Fresnel Zone blockage introduces UTP cables. Communication with these devices is performed little signal loss to the link. Beyond 40% blockage the signal using the TCP / IP protocol. RF connectors are connected to loss will become significant. the measuring device using special RF cables. The computer is running agent software for communications with the measuring device and the RF transmitter adjusting system. FSPLr = 17.32 d / 4 f (3) The system deployment diagram is shown in Fig. 1. here: d - distance [km], f - frequency [GHz], r - radius [m]. Following the model proposed by Ocana et al. [Ocana], the WiFi map can be calculated using a radio propagation model. This model is difficult to obtain for indoor environments, due to multipath effects and temporal variability of the WiFi signal. RSL = TSL + GTX + GRX + (4) 20log ( 4λ ) − 10nWlog ( d ) − X a here RSL is the received signal level, TSL is the transmitted signal level, GTX and GRX are the transmitter and receiver Fig. 1. Package diagram of an experimental system antennas gain respectively, λ is the wavelength (12.5cm for the 2.4GHz of the WiFi signal), nW is a factor that depends on the walls effect, Xa is a random variable and d is the distance V. MEASURED VALUES between the emitter and the receiver [42]. Using the developed system prototype we measure: 1) The number of access points visible from a device. 2) The signal VI. CREATION OF WIFI MAPS strength of the strongest field. 3) Aggregate signal strength. Creating a WiFi signal coverage map for a given Attenuation can be defined as the decrease of the transmitter using this approach involves: (1) fitting a amplitude of a signal between its transmission and reception semivariogram function, which describes the amount of points. As the radio waves propagate through the air it loses expected variation as a function of distance between power over a distance. Therefore signal strength is less. The measurements and (2) predicting the value at each unmeasured loss a signal will undergo between the transmitter and receiver location (pixel). is referred to as Free Space Path Loss (FSPL). FSPL can be understood as power lost as energy disperses into the air. Wi-Fi mapping is based on the signal scanning in different FSPL depends on two parameters: the frequency of radio places at different times. Ideally, measuring the signal strength signals and the wireless transmission distance. The following of all possible points at the same time allows to obtain the formula can reflect the relationship between them: perfect Wi-Fi access point (Access Point, AP) map. However, in practice signal values are measured only in a number of selected location points, while in other points the signal values FSPL ( dB ) = 20log10 ( d ) + 20log10 ( f ) + K (1) are interpolated α +toβ create = χ. large (1)areas (1) of maps. Such WiFi mapping has many uses such as for open access points search; signal versus time comparison; finding the signal problem areas; and optimizing the coverage area. 53 Time signal detection and interpretation must be carried assess dynamical changes of AP coordinates at some point in out within the time for all supported frequency band. In order time. to evaluate the signal quality is assessed the following • Radio map (radio-map) constructs a map by measuring parameters Signal to Noise Ratio (SNR), and Signal to Interference Ratio (SIR). Since packet data networks are the signal strength to a number of points. This technique is used for internal mapping and usually requires 2 stages. The prevalent in wireless networks therefore one needs to assess and receive data transmission at higher layers. Since the first stage is to collect AP signal strength at predetermined points of location and save them to the database. In the second higher layers are analyzed to transmit data, so they need to be checked for each channel or frequency after they arrive. stage, the signals are compared and the most likely signal at each site used as a good signal for display. Wireless networks have different frequencies each with the further frequency width, which may be 5, 10, 20 or 40 MHz After collecting the data described above is possible the wide. In assessing signal quality is necessary to take into data shown on the map in different ways: account these parameters. Wi-Fi mapping is necessary to evaluate the signal in different places, and to do so at different 1. Survey Map - signal analysis map to display data frequencies. collection points and signal strength in these points. The WiFi signal detection procedure is shown in Fig. 2. 2. AP Signal heatmap – shows signal strength variation in The data collected can include SSID: Service Set Identifier; space except only at one selected access point, and all other MAC address: AP identifier; Signal strength: the access point access points are ignored. Interpolation is used to obtain full signal strength; Quality: the strength of the surrounding access map coverage. points; set of parameters describing the connection quality; 3. Signal heatmap - displays the total number of access Longitude and Latitude of AP coordinates. points and variation of the signal strength in space. 4. AP Coverage – the map divided into zones, featuring dominating point. Also signal strengths are measured, assessing all the signals with a power greater than 70dBm. 5. Frequency, data speeds and other parameters of signal strength maps representative of two or more of the selected attributes dominance zones and overlapping areas in assessing the strength of the signals which exceed the predetermined values. VII. RESULTS IN WIFI MONITORING Due to the small number of transmitting devices in the area, it is not possible to apply simple propagation models, such as free space, to relate the received power to distance. For this reason, we need to consider more complex propagation models accounting for the geometry of the environment. Here we consider the multiwall path loss model [43] which accounts for propagation at 2.4 GHz. It is based on generalization of the classical one slope loss model including an additional attenuation term due to losses introduced by the walls and floors encountered by the direct path between the transmitter and the receiver. The signal power is defined as: I Nd N fd M w = lc + ∑ kwi li + ∑ χ n ld + ∑ λn l fd , (5) Fig. 2. Algorithm of WiFi signal capture i =1 n =1 n =1 After collecting this data, WiFi maps can be formed in where lc is a constant, kwi is the number of penetrated walls many ways, such as maximum bandwidth, minimum delay, of type i, li is the attenuation due to the wall of type i, i = 1, 2, the best coverage, etc. Wi-Fi detection techniques can be . . . , I, Nd and Nfd are the numbers of normal and thick doors divided into two groups: encountered by the direct path, and χn(λn) are binary variables accounting for the state (opened or closed) of the n-th door. • Model-based (model-based) uses the detected signals AP locations and radio frequency measurement model as The data was obtained by the authors within the office triangulation help from all the points determined by the access building of Kaunas University of Technology (KTU). The point location. This technique has the great advantage of the experimental results of modeling the SAR values of WiFi external mapping. Mapping is a long process, and using this signals are presented in Figs. 3, 4 & 5, respectively. technique, a small amount is sufficient to find enough points with precise AP coordinates. However, the model is unable to 54 most by the features of the building thus provided safer locations for office workers, e.g., for placing permanent work places such as office desks (see Fig. 5, see a lighter shaded area at the top right corner of the building). VIII. CONCLUSIONS WiFi needs to be used intelligently due to health concerns. This involves limiting the spatial range of exposure, establishing WiFi-free areas, providing wired access to those who choose not to use wireless, and limiting the duration of exposure in public spaces. The developed prototype allows measuring the WiFi field strength and constructing WiFi signal maps in public spaces. Using such maps one can plan the layout of work desks in offices, or tables in cafes to minimize prolonged exposure to high frequency EM radiation. 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