Smart Ice Prevention System to Improve Effectiveness and Reduce Energy Cost

Alison M. Siegmann, Michael F. Algieri, and Douglas E. Dow Program in Electromechanical Engineering, College of Engineering

Wentworth Institute of Technology

Senior citizens are at a higher risk of both falling and fall related fractures. This risk is particularly high during the winter months in northern climates due to slipping on ice and snow of inclement weather conditions. Two approaches are typically used to reduce the buildup of ice and snow including sanding or salting steps and walkways, and installing heating mats. These mats can function by electrically heating rubber treads fixed to outdoor stairs and walkways. The currently available mats have to be manually turned on or plugged in order to work. This may result in either the mat remaining off and the snow accumulating, or the mat would be on for an unnecessarily long time, wasting energy and related costs. A product with no automatic feature could cause a problem when someone has to wait two to three hours for the snow to melt, or the person may try to go through the snow before the ice and snow all melts risking injury.

The purpose of this project was to develop and test modules for a smart heating system with the ability to sense when the conditions are right for snow and ice to form and to automatically turn the heating mechanism on and off within the mat. This should result in a more safe and dry walkway using only the necessary amount of energy. A combination of temperature, humidity, and weight sensors will be monitored by a program to determine whether or not there is a risk of ice to form. The program will then control the heating mat. Successful development of this project could result in fewer falls due to poor conditions for the elderly.

Introduction/Background

Senior citizens are at a higher risk of both falling and fall related fractures especially in the winter months. Hip and arm fractures are the most common fall related injury for the elderly1. Domestic accidents for senior citizens often have serious consequences; 57% of domestic accident cases result in one or more fractures and 24% require hospitalization2. Pedestrian falls which resulted in hospitalization spent an average of 8 days in the hospital accruing large medical bills3. This risk is particularly high during the winter months between October and March in northern climates, primarily due to slipping on ice and snow1. This study compared the number of fall related fractures during the summer months to the number of recorded incidents during the winter months. The number of occurrences for arm fractures was 69% higher during the cold seasons, while the number of hip fractures was 27% higher1. Reducing the risk of snow and ice forming where elderly people walk would reduce the risk of

injury, especially in high risk locations such as steps and walkways.

Two approaches are typically used to reduce the buildup of ice and snow on the surfaces. These approaches include sanding or salting steps and walkways, and installing heating mats. For cases of significant snowfall, the spreading of salt and different kinds of chemicals on the surface to melt the snow and ice would not be effective without first shoveling. Many elderly people hire maintenance workers to come and shovel their walkways, but are dependent on the schedule of those workers that may or may not coincide with the weather patterns or the senior’s schedule.

Spreading salt on stairs and walkways causes a host of problems, even if the area is properly shoveled. Road salt can damage wildlife, affect water quality, and cause corrosive damage to cars and surfaces both inside and outside of buildings. Salt spread on roads damages vegetation by increasing the water stress, reducing the quality of the soil, and accumulating chloride components causing increased toxicity levels within plants4.

Consumption of plant products that have been affected by road salt can increase the risk of various health problems causing various health problems for animals. Birds may eat small amounts of salt which can cause toxicosis and death5. Many pets that eat or drink the snow melt may become fatally ill. Salt can lead to painful irritations and cracking of the paw pads for dogs and cat6. Water quality is also reduced due to road salt entering into water streams and creating a benthic saline layer which then affects the water quality and ecology of many different bodies of water7. Salt may also cause corrosion on the body of cars, this rust results in a shorter lifetime for the parts affected8.

Heating mats are commercially available today; these mats function by electrically heating rubber treads fixed to outdoor stairs and walkways. Heattrak (Heattrak LLC, Paterson, NJ) produces heating mats for both stairs and walkways. The stair mats measure 10” x 30” and draw 0.7 amps, the walkway mats measure 60” x 20” and draw 2.5 amps9. These mats can melt snow at a rate of approximately two inches per hour9. This product appears to have many advantages but could be improved with some innovation, especially for use by the elderly. Disadvantages with this kind of device are the cost of the product, the energy consumption for the homeowner, the time needed to melt the snow and ice, and effective timing of when to turn on the device or off. Each walkway mat sold by HeatTrak costs $139.95 and each stair mat costs $59.99. In addition, power units must be purchased for the heating system to be function, these power units cost $34.959. The instalment costs are relatively low compared to the cost of hiring a maintenance worker to manually shovel the sidewalks. However, there is a hidden cost involved with this product, the cost of electricity used to heat the mat. One issue with such systems is the control to turn the heating mechanism on or off. The currently available mats have to be manually turned on or plugged in order to work. Many elderly people even forget to turn off lights in their house so they would have trouble remembering to turn on the mats at the start of precipitation. Thus either the mat would not be turned on and the snow would not melt, or the mat would be heated for an unnecessarily long time, wasting energy and related costs. A product with no automatic feature could cause a problem when

someone has to wait two to three hours for the snow to melt, or the person may try to go through the snow before the ice and snow all melts, risking injury.

In this paper we propose a solution for this problem, to develop a smart heating system with the ability to sense when the conditions are right for snow and ice to form and to automatically turn the heating mechanism on and off. The heating mechanism will be located in a mat fixed to stairs or walkways. A combination of temperature, humidity, and weight sensors placed within the mat will be monitored by a program to determine whether or not there is risk of ice to form. The program will provide the user with settings options and control the heating of the mat in order to reduce risk of ice forming while being energy efficient. The system will be able take data from and control 1 to 10 stair mats connected in series.

Toward this proposed solution an important module is the interface between the sensors, software, and the outside world.

The purpose of this project is to develop and test modules for a smart heating system for stairs and walkways. Once this subsystem is tested, the design can be easily expanded to include the entire system. The prototype will include the temperature, humidity, and weight sensors and will test the accuracy of the sensors as well as the program’s ability to take the inputted data and determine whether power should be sent to the mat.

This should result in a more safe and dry walkway using only the necessary amount of energy. Successful development of this project could result in fewer falls due to poor conditions for the elderly.

Formulation/Methodology Design

The design for smart ice prevention system is comprised of two modules including the software module and sensor module. The final design will combine these two modules to create a complete system. The system takes into account three physical parameters in order to determine whether there is risk of ice to form including the air temperature and humidity as well as the accumulation of snow or ice on the mat. The air temperature and humidity determine if there is risk of ice to form, the weight sensor determines

Figure 1. Software Module Flowchart

whether there is snow on the mat. The weight sensor is responsible for shutting off the system when the ice has completely melted off the mat.

The initial software module was a software only system written in LabVIEW (National Instruments, Austin, TX) which accepted manually adjusted values for temperature, humidity, and weight. These values were then analyzed in the algorithm to determine whether they were above or below their respective threshold values. The threshold value for the temperature sensor was set to 35°F (1.7°C), this value was chosen to be above the freezing point of water due to the ability for snow form in the atmosphere when the ground temperature is above freezing. The threshold value for the humidity sensor was set to 80%, when air humidity is above this value there is enough moisture in the air for water to condense and form ice. The weight threshold was set to 1.5 pounds (0.68 kg) over the entire mat. Snow typically

weighs 15 pounds per cubic foot (240.3 kg/m3), although snow may be heavier or lighter depending on is composition. The threshold value was determined by estimating the weight of half an inch of snow covering the stair mat. In order to increase the accuracy of the system and reduce the amount of time the mat is receiving power without snow or ice being present one of two conditions must be met. The temperature must be below the threshold value and either the humidity must be above the threshold value or the weight on the mat must exceed its threshold value. When the conditions to turn the mat on are met an indicator LED is lit to represent power being sent to the mat. The temperature, humidity, and weight data is saved in a file as well as whether the mat was turned on or off in order to help the user track its usage and power consumption. Figure 1 illustrates the software flow chart.

The sensor module was comprised of the temperature, humidity, and weight sensors. The selected humidity and temperature sensor was model RHT03 (MaxDetect Technology Co., Ltd., Shenzhen, China). This sensor outputs digital values. The specified range of -40℃ to 80℃ and 0 to 100% humidity was considered adequate. The weight sensor chosen was the SEN-09376 (Interlink Electronics, Camarillo, California). This force sensitive resistor has a sensing area is a 1.75 inch square and measures masses in the range of 0.22lb to 22lb. An Arduino Uno microcontroller system (Arduino, www.arduino.cc) was used to collect and analyze the output of each sensor.

The complete design combined the software and sensor modules to create the smart system. The sensors input real time data to the LabVIEW program through the Arduino, the program then analyzed this data and determined what state the mat should be in. The combined system included a relay controlled by the LabVIEW program which controlled the power AC current flow to the mat. When the software determined the heating mat should be turned on the relay was set to allow current to flow into the mat, when the mat should be turned off the relay acted as a switch to stop the current flow. Testing Methods

The software module was tested by manually changing the temperature, humidity, and weight values and observing the output LED. These values were manually entered in order to test only the software module without any possible errors from the sensor outputs. The temperature, humidity, and weight values inputted spanned the entire range for each parameter with special emphasis testing above and below threshold values.

The sensor module was tested by testing each of the three sensors individually. The weight sensor was tested by connecting the output to a digital multimeter and monitoring the change in resistance with different weights. Weights ranging from 0.22lb to 2.2lb were tested. The temperature and humidity sensor was tested by placing the sensor in an environment where the temperature and humidity was known and monitoring the output. With each environmental change the sensor was left for a minimum of 20 minutes in order for the

sensor to adjust to the temperature of the surrounding environment.

The combined system will be tested by placing the sensors in different environments and varying the load on the weight sensor and monitoring LED indicator in the program. The test will be deemed as successful if the LED lights when either of the two conditions stated above are met and if it is off otherwise.

Analysis and Results

The software module worked as expected. Table 1 illustrates the data taken during testing including the sensor values and the output of the LED. When the LED is on the mat condition value is 1, and when the LED is off the mat condition value is 0. In each sensor value combination, the LED responded as expected.

The weight sensor testing results are listed in Table 2. The trials were repeated four times. As expected, the resistance decreased as the load increased and there were discernable differences in resistance with different loads. Table 3 displays the testing data for the temperature and humidity sensor in different environments. Due to limited access to a calibrated humidity sensor the data for the temperature and humidity sensor is limited. More testing will be done in the future in more diverse environments.

The combined system was tested under various conditions, results from the testing are listed in Table 4. The system was tested by changing the temperature and humidity of the environment while keeping the weight constant in order to test the mat condition involving the temperature and humidity. Then the temperature was held constant while the weight was changed in order to test the mat condition involving temperature and weight. As shown the mat responded correctly to each set of conditions.

Table 1. Software Module Testing Results

Date / Time Weight (lbs.) Temperature ( ̊F) Humidity (%) Mat Condition

(On=1, Off=0)

3/17/2016 15:03 0.92 31.23 85.71 1

3/17/2016 15:04 0.92 40.68 85.71 0

3/17/2016 15:04 0.92 49.31 85.71 0

3/17/2016 15:04 0.92 49.31 6.12 0

3/17/2016 15:04 0.92 49.31 66.32 0

3/17/2016 15:05 0.92 49.31 74.48 0

3/17/2016 15:05 0.92 49.31 81.63 0

3/17/2016 15:05 1.33 49.31 80.61 0

3/17/2016 15:05 1.53 36.98 33.67 0

3/17/2016 15:05 1.53 34.52 33.67 1

3/17/2016 15:06 1.02 34.52 80.61 1

3/17/2016 15:06 1.02 27.94 21.42 0

Weight (lbs.)

Resistance Reading 1 (Ω)

Resistance Reading 2 ((Ω)

Resistance Reading 3 (Ω)

Resistance Reading 4 (Ω)

0 Overload Overload Overload Overload

0.022 0.46 M 0.154 M 0.166 M 0.158 M

0.044 37.7k 40.2 k 37.8k 38.5k

0.11 14.5k 13.8k 12.6 11.6

0.22 8.2k 9.1k 8.0k 6.85k

0.44 3.7k 3.63k 3.3k 2.9k

1.10 2.0k 2.3k 1.77k 2.08k

2.20 0.966 1.0k 0.936k 0.822k

Table 2. Weight Sensor Testing Results

Conclusions and Future Directions

Results from the testing for the prototype show that the design has promise to successfully melt snow off stairs and walkways, making travel in and out of the house safer. The results of the early testing for the prototype show that the design has promise for accurately measuring the temperature and humidity in an environment, as well as the weight on the mat. Software testing showed the ability of the program to determine whether the mat should be heated.

The next steps for this project include

integrating the sensor and software modules into the heating mat module. Three weight sensors will be placed in each mat for testing as shown in exploded view in Figure 2.

Environment Temperature (°F)

Environment Humidity (%)

Sensor Temperature (°F)

Sensor Humidity (%)

75.4 43.7 74.6 42.8

76.5 -- 76.46 28.6

77.0 40.7 76.64 40.6

Date / Time Weight (lbs.)

Temperature ( ̊F) Humidity (%) Mat Condition (On=1, Off=0)

4/12/16 18:05 0 23 20 0

4/12/16 18:05 2.2 28.6 18 1

4/12/16 18:07 0 32.4 17 0

4/12/16 18:10 0 48.2 38 0

4/12/16 18:15 0 57.2 23 0

4/12/16 18:20 0 62.8 38 0

4/12/16 18:32 .5 62.8 37 0

4/12/16 18:38 .7 62.8 37 0

4/12/16 18:43 1.0 62.8 35 0

4/12/16 18:50 0 64.4 29 0

4/12/16 18:54 .75 69.8 33 0

4/12/16 18:58 0 71.6 33 0

4/12/16 19:05 0 28.4 86 1

Table 3. Temperature and Humidity Sensor Testing Results

“--“indicates no humidity data was available

Table 4. Combined System Testing Results

Figure 2. Exploded View of Heating Mat Module

The software module will be modified in order to take data from the three weight sensors in each mat as well multiple mats connected together. When multiple mats are connected the software will require at least two of the mat weight sensors to be tripped in order to turn the heating system on. This will prevent the mats from turning on when an object is left on the steps. The mats will then be placed on steps and connected to one another as shown in Figure 3.

Figure 3. Complete Assembly of Heating Mat

The testing that has been conducted up to this point on the software and sensor modules as well as the combined system has been successful. The combined system successfully determined the condition the mat should be in based on the surrounding environment, this system integrated into the heating mat should result in safer walkways for elderly homes. Further development

and testing will be necessary toward wide application of the heating system.

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