Author Archives: Richard Le

Group 4 Conclusion

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What were your results?

All the trials-including the RF meter trial-demonstrate the highest amount of readings 1 meter away from the wireless access point (WAP), and as expected, all three trials show a negative association between distance and dBm. As previously mentioned, these are the circumstances for each of the trials:
Trial 1: WAP uncovered.
Trial 2: WAP covered with cinder block.
Trial 3: WAP covered with cinder block and surrounded by 12 wood planks.
Trial 4: RF electrosmog meter used, WAP uncovered.

Descending Values

We expected the signal strength to descend from Trial 1 to Trial 3, but instead, Trials 2 and 3 alternated in dominant strength between distances. There was an even split in averages, with 5 distance points of Trial 2 dBm readings being greater than Trial 3 dBm, and with 5 distance points of Trial 3 dBm readings being greater than Trial 2 dBm readings. Because of this even split, we are hesitant in reporting that increasing the volume of medium to an already-covered WAP decreases the signal strength.
A peculiar observation to note is that from 2 meters, trials 2 and 3 gave dBm readings that were significantly lower than the data of trial 1. Trial 1 at 2m yielded an average of -41.6dBm, while Trial 2 yielded -49.4dBm and Trial 3 yielded -50.6 dBm. The 2m was the distance that showed the largest gap in signal strength between Trial 1 and 2-3. Continue reading →

Group 4 Project Data

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Data Collection Methods:

Our router in trial 3, with full enclosure

We set up our experiment in the Raymond MPR, laying out tape in 1m intervals, and placing the router on the floor. We placed the measuring instruments on a table and moved the table 1m back when we had taken enough data at each distance.

Trials 1-3: Using an Android cell phone with the app Wi-Fi Analyzer, we recorded the signal strength of the wireless access point (WAP) from 1-10 meters. The app scans for networks and reports the signal strength, every 5 seconds. Data was taken at 5 second intervals, in which the cell phone app refreshes its readings.

A diagram of our experiment.

Router Conditions for Trials 1-3

In order to modulate our variable, we increased the volume of the medium being passed through by the wireless radio signals during each trial.

Trial 1: WAP uncovered.

Trial 2: WAP covered with cinder block.

Trial 3: WAP covered with cinder block and surrounded by 12 wood planks.

Trial 4: WAP uncovered.

Trial 4: RF Meter used to record mW/m² values. The meter was used on its instantaneous value setting and records values rapidly, so table data was taken in 5 second intervals.

Explanation of Data

In order to make it easier to recognize trends, we took the averages of the 5 data values taken at each distance for trials 1-4 and used those for graphing. We believe that graphing average values is the most logically sound and clear way to represent our data, as the readings for both power density and power tended to fluctuate greatly, making instantaneous values unreliable to graph.

The general trend in our data measurements is that the average power density and power tends to decrease as we increased the amount of obstacles, as we would intuitively guessed. However, it is interesting to note that the trend of the averages in fig 4 has an interesting behavior. At around 9 meters, the readings dip to their lowest values before returning to a higher value at 10m. We suspect that this may relate to the wave reinforcement and/or cancellation— the reflective/absorbent properties of Raymond MPR’s various materials and geometric shape is probably to blame for this peculiar anomaly.

Trial 4 data was not averaged with the other trial data on fig. 4 because the units being compared are not effectively comparable (dBm vs. mW/m²). We found the data for trial 4 to be problematic and unreliable because of the extremeness in fluctuation of the data given by the RF meter. However, the sharp cutoff from 1m to 2m may reveal that radio signals have an unexpectedly steep cutoff. Because of this, smaller increases in distance at this specific cutoff distance (found to be somewhere between 2-3m) may result in great loss of power density. However, this is only a conjecture, as we are wary of giving legitimacy to this data set because the volatile behavior of the RF meter.

Units

mW/m² – Power density (milliwatts per meters squared)

dBm – Power, expressed in a logarithmic ratio (decibel-milliwatt)

m – Distance, standard SI base unit (meters)

Data Tables

Trial 1, without block.
Distance	A	B	C	D	E	Average
1	-42	-39	-36	-38	-41	-39.2
2	-44	-41	-41	-41	-41	-41.6
3	-42	-38	-41	-41	-38	-40
4	-41	-41	-41	-44	-41	-41.6
5	-41	-41	-41	-47	-41	-42.2
6	-41	-44	-50	-47	-50	-46.4
7	-44	-47	-47	-44	-47	-45.8
8	-53	-50	-47	-50	-59	-51.8
9	-56	-53	-50	-56	-53	-53.6
10	-53	-47	-53	-47	-53	-50.6
Trial 2, with cinder block only
Distance	A	B	C	D	E	Average
1	-42	-35	-41	-35	-41	-38.8
2	-47	-50	-53	-50	-47	-49.4
3	-48	-41	-44	-50	-41	-44.8
4	-44	-47	-50	-47	-41	-45.8
5	-44	-50	-47	-47	-41	-45.8
6	-48	-47	-44	-50	-50	-47.8
7	-47	-50	-47	-53	-47	-48.8
8	-50	-56	-50	-56	-59	-54.2
9	-59	-53	-56	-59	-53	-56
10	-47	-56	-50	-53	-53	-51.8

Trial 3, with cinder block + 12 wood surrounding
Distance	A	B	C	D	E	Average
1	-41	-35	-35	-41	-35	-37.4
2	-50	-53	-50	-47	-53	-50.6
3	-44	-50	-41	-44	-41	-44
4	-44	-41	-44	-47	-50	-45.2
5	-41	-44	-50	-44	-44	-44.6
6	-53	-44	-50	-47	-53	-49.4
7	-53	-56	-56	-50	-50	-53
8	-56	-53	-56	-56	-53	-54.8
9	-59	-53	-56	-59	-53	-56
10	-57	-54	-51	-60	-51	-54.6

Trial 4 RF Meter
Distance	mW/m2					Average
1	1168	1356	1701	1397	2136	1551.6
2	401.3	300.8	345.2	291.4	380.5	343.84
3	211.7	229.6	205.8	190.7	246.6	216.88
4	69.4	105.6	87.4	70	116.4	89.76
5	132.5	88.6	105.4	176.4	235.8	147.74
6	32.4	71.6	43.5	39.2	180.5	73.44
7	44.6	51.1	67.4	57.7	33.8	50.92
8	96.8	328.8	76.3	141.6	274.8	183.66
9	31.1	41.6	89.6	35.7	27.2	45.04
10	59.9	74.9	5.8	131.4	60.2	66.44

Data Graphs/Visualizations

: Figure 1

: Figure 2

: Figure 3

: Figure 4

: Figure 5

Group 4 – Wi-Fi Penetration through a Medium – Project Plan

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Roles:

Charlie – Collect/manage data, location scouting, manage materials, research information

Richard – Collect/manage data, presentation editing work, file management, research information

Equipment/Supplies:

TES-593 electrosmog meter
Cell phone (with application for displaying dBm reading)
Wood blocks
Router
Laptop computers (used for documentation and data organization/presentation)

Science/Technology involved:

We will be examining the nature of a specific wireless communication technology known as Wi-Fi. Wi-Fi is a technology used in every almost personal device that accesses the Internet. It uses radio technologies called 802.11, and occupies specific bands of the radio spectrum: 2.4gHz and 5gHz. (Reference)

Radio power levels are measured in decibels (dB), which Cisco Systems defines as “the power of a signal as a function of its ratio to another standardized value.” Our consumer devices often give a reading of the signal strength as (dBm), which is a value compared with milliwatts. (Reference)

Activity Plan

We will be utilizing a TES-593 electrosmog meter. The meter is capable of measuring radio frequency (mV/m,V/m), magnetic fields (µA/m, mA/m), and power density (µW/m², mW/m², W/m², µW/cm², or mW/cm²). The frequency range for the ElectroSmog Meter is 10MHz to 8GHz. With the electrosmog meter, we will be measuring power field density.

To measure electrical power, we will be using a cell phone or laptop, which will provide readings in dBm

First, we will find a location where there is minimal outside interference.

Before we record our data, we will take a control value that accounts for ambient RF activity, since there will most likely be some sort of RF activity present in any locations on campus, due to the high concentrations of RF-emitting devices on campus (wireless networks, cell phones, radio towers, etc…).

When a test location is found, we can set up our experiment.

The router will be placed on one side of the room and powered on to broadcast a network that we will be connecting to in order to gauge its strength.

On the opposite side of the room, we will set up our receiving/measuring devices, which we will use to record data. Our laptops and our cell phones will be used along with a program that will allow us to measure the dBm readings. We will increase the volume of the wood blocks in front of the router and in front of the device, and record the changes in data.

Project Dates:

9/23, 2-4PM; 9/26, 4-6PM; 9/27, 5-7PM; 10/1, 4-6PM

Outcomes:

We believe the general trend will be a decrease in power field density (mW/m2) and a decrease in power level (dBm) that is related to an increase in the volume of the wood— a variable we will be altering and observing.

Group 4 Project Abstract

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A brief analysis on the effect of signal penetration through increasing volume of a medium.

Many members of the Vassar community, students and faculty alike, occasionally experience issues with our wireless connections across campus. There are many variables as to why the connection in our rooms may be inferior to the connections in other locations on campus— RF interference, distance from the connection source, for example. However, a particular phenomena that our project seeks to elucidate is the effect of different materials on the quality of Wi-Fi reception. Our project examines the relationship between the loss of wifi/RF signal strength and the change of volume of a single type of material. This material that we use will be our sole variable. Our hypothesis is that by increasing the volume of our chosen material (wood, in this project), we will diminish the strength (and consequently, quality) of the Wi-Fi connection we will be measuring.