The slides and writing content for the midterm project
Overview
The topic for our project is “NYC Anxiety Map”, the general goal is to create a tool for NYC dwellers to better manage their anxiety, which we hope will lead to more pleasant interactions and an increase in the overall emotional health of the city. The expected implementation process should be based on sensors and a geo-locator, users can see their anxiety levels displayed on a map, lending transparency to what time/location may be triggering their anxiety, as well as patterns they can better prepare for. The device will take pulse/heart rate, as well as noise, into account.
Significance
With the development of economy and society, the urbanization comes to be normal phenomenon around the world, the bad impacts caused by the urbanization and exploding cities should be the potential psychological problems, for examples, fury, depression and anxiety. Each of them will do bad impacts on people’s emotional health. And our project aims at providing a possible way for people to manage their anxiety level through detecting some physical index by sensors. The problem of overweighed anxiety is expected to be tackled by getting people be aware of and be warned with their anxiety level, and then take some corresponding measures.
The core concept of our project should be affective computing, it is a popular area with increasingly attention and has been researched around the world for several years. Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. Detecting emotional information begins with passive sensors which capture data about the user's physical state or behavior without interpreting the input. The data gathered is analogous to the cues humans use to perceive emotions in others. The emotional information we focused in the project should be skin condition and pulse/heart rate. As for some prior works of the affective computing, there are typical examples. The Cognition and Affect Project (University of Birmingham), Blue Eyes (IBM) and Affect Sensitive Human-Robot Collaboration (Vanderbilt University), these prior projects are all focused on affective computing and extract crucial information to support the emotional management and decision making.
Quantified Self
First of all, we are going to collect enough sample data inside New York City, and the anxiety map formulated could be a great reference for the dwellers in NYC, the map is going to show a general or average anxiety condition of NYC, it is expected to help people pay attention to mange their emotion in some specified areas and around some specified time points. Secondly, as we are making the devices wearable in the future, so it offers people easier ways to monitor their anxiety based on real-time data, for example, since the device is connected with the mobile applications, the app can be designed to give warnings when the anxiety index gets over than a specified value. Through the comparisons between different areas and time periods, people are expected to know the main factors causing their anxiety, and take corresponding measures.
Smart City/Communities
As mentioned in last part, enough sample data will be collected to formulate the anxiety map, the map also comes to be a great reference for the government and public health department. When the map shows a general or average anxiety condition of NYC, the government may plan for the public psychological guidance based on the map, for example, if the anxiety level is relatively high around rush hour before or after work, the government may consider staggering the working hours. Also, as one of the index we are going to detect, the noise comes to be important for the city and community. If the noise is positively correlated to the anxiety level, the city agencies or government may take controls of the traffic noise, construction noise and other origins of noise, especially in the “red time” when the anxiety level tends to be high.
Furthermore, when the device keeps collecting data from individuals in the future, the changes will be directly shown on the interactive map, for governments, it is a true reflection on whether the measures taken by government are effective and efficiency, the government can adjust the plans according to the map.
Prototyping Usability
The usability is our biggest hurdle. In order to be an effective tool to collect data which can be directly utilized by the visualization tools, the device must be mobile. Currently, the device is static, but our next iteration will utilize the Bluefruit-LE to enhance mobility. Additionally, we would like to build a case for the device, so it can be stored easily on a user during use. We will need to explore whether the device should be wearable or simply kept in a pocket.
Future Work
Firstly, we are going to address the potential challenges to make the project perfect. On the on hand, make it wearable thus collecting data can be much more efficient and accurate, also it’s great developing direction for the project because we expect that people can monitor their anxiety and supervise themselves. On the other hand, we have to find out whether a rise in heart rate is due to anxiety or, for example, exercise, although this could be a normal error is a general test yet we have to figure out some ways to make the data accurate.
Secondly, we are considering whether it is possible for us to develop a simple mobile app to offer people legible and intelligible information, for example warnings and some tips for health based on the collected data. It is an important process to interpret the data for users.
The topic for our project is “NYC Anxiety Map”, the general goal is to create a tool for NYC dwellers to better manage their anxiety, which we hope will lead to more pleasant interactions and an increase in the overall emotional health of the city. The expected implementation process should be based on sensors and a geo-locator, users can see their anxiety levels displayed on a map, lending transparency to what time/location may be triggering their anxiety, as well as patterns they can better prepare for. The device will take pulse/heart rate, as well as noise, into account.
Significance
With the development of economy and society, the urbanization comes to be normal phenomenon around the world, the bad impacts caused by the urbanization and exploding cities should be the potential psychological problems, for examples, fury, depression and anxiety. Each of them will do bad impacts on people’s emotional health. And our project aims at providing a possible way for people to manage their anxiety level through detecting some physical index by sensors. The problem of overweighed anxiety is expected to be tackled by getting people be aware of and be warned with their anxiety level, and then take some corresponding measures.
The core concept of our project should be affective computing, it is a popular area with increasingly attention and has been researched around the world for several years. Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. Detecting emotional information begins with passive sensors which capture data about the user's physical state or behavior without interpreting the input. The data gathered is analogous to the cues humans use to perceive emotions in others. The emotional information we focused in the project should be skin condition and pulse/heart rate. As for some prior works of the affective computing, there are typical examples. The Cognition and Affect Project (University of Birmingham), Blue Eyes (IBM) and Affect Sensitive Human-Robot Collaboration (Vanderbilt University), these prior projects are all focused on affective computing and extract crucial information to support the emotional management and decision making.
Quantified Self
First of all, we are going to collect enough sample data inside New York City, and the anxiety map formulated could be a great reference for the dwellers in NYC, the map is going to show a general or average anxiety condition of NYC, it is expected to help people pay attention to mange their emotion in some specified areas and around some specified time points. Secondly, as we are making the devices wearable in the future, so it offers people easier ways to monitor their anxiety based on real-time data, for example, since the device is connected with the mobile applications, the app can be designed to give warnings when the anxiety index gets over than a specified value. Through the comparisons between different areas and time periods, people are expected to know the main factors causing their anxiety, and take corresponding measures.
Smart City/Communities
As mentioned in last part, enough sample data will be collected to formulate the anxiety map, the map also comes to be a great reference for the government and public health department. When the map shows a general or average anxiety condition of NYC, the government may plan for the public psychological guidance based on the map, for example, if the anxiety level is relatively high around rush hour before or after work, the government may consider staggering the working hours. Also, as one of the index we are going to detect, the noise comes to be important for the city and community. If the noise is positively correlated to the anxiety level, the city agencies or government may take controls of the traffic noise, construction noise and other origins of noise, especially in the “red time” when the anxiety level tends to be high.
Furthermore, when the device keeps collecting data from individuals in the future, the changes will be directly shown on the interactive map, for governments, it is a true reflection on whether the measures taken by government are effective and efficiency, the government can adjust the plans according to the map.
Prototyping Usability
The usability is our biggest hurdle. In order to be an effective tool to collect data which can be directly utilized by the visualization tools, the device must be mobile. Currently, the device is static, but our next iteration will utilize the Bluefruit-LE to enhance mobility. Additionally, we would like to build a case for the device, so it can be stored easily on a user during use. We will need to explore whether the device should be wearable or simply kept in a pocket.
Future Work
Firstly, we are going to address the potential challenges to make the project perfect. On the on hand, make it wearable thus collecting data can be much more efficient and accurate, also it’s great developing direction for the project because we expect that people can monitor their anxiety and supervise themselves. On the other hand, we have to find out whether a rise in heart rate is due to anxiety or, for example, exercise, although this could be a normal error is a general test yet we have to figure out some ways to make the data accurate.
Secondly, we are considering whether it is possible for us to develop a simple mobile app to offer people legible and intelligible information, for example warnings and some tips for health based on the collected data. It is an important process to interpret the data for users.