Outcome

Intent

CoinMind is a unique and innovative project that aims to combine the ancient practice of divination with modern technology. Specifically, the project employs the principles of the I Ching, an ancient Chinese divination system that is based on the concepts of Yin and Yang.

Users of CoinMind toss a coin six times inside a box, with the left side colored white to represent Yang and the right side colored black to represent Yin. The machine analyzes the results of the coin tosses and generates insights into the user's future based on the hexagrams of the I Ching. These insights are displayed on an LCD screen, with an image that represents the fortune followed by text that explains the image.

The big ideas behind CoinMind include the fusion of old and new technologies, the importance of traditional wisdom in a rapidly changing world, and the potential of divination as a tool for personal growth and self-discovery. The goal of this project is to provide users with an easy-to-use and accurate tool for accessing the wisdom of the I Ching.

By combining the ancient ritual of coin tossing with modern technology, CoinMind offers a unique way for people to engage with the I Ching and deepen their understanding of traditional wisdom. Ultimately, the project aims to promote a broader appreciation of the value of traditional wisdom in our modern world and to encourage personal growth and self-discovery through divination.

Context

CoinMind draws inspiration from prior work in coin-tossing divination rituals. Two examples of prior work that influenced our design are the I Ching, an ancient Chinese divination system, and the Tarot, a deck of cards used for divination purposes. The work that informed this idea includes research on the use of technology for divination and self-discovery, as well as the application of traditional wisdom in modern contexts. The theory and concepts that relate to the outcome of this project include the principles of the I Ching, which are based on the concept of Yin and Yang, as well as the importance of traditional wisdom in a rapidly changing world.

Additionally, the application of concepts from human-computer interaction and design played a crucial role in shaping the user experience of the CoinMind predictor. For instance, the use of an LCD screen to display the results of the coin tosses and the design of the box that holds the coin are both informed by principles of design and user experience to create an engaging and intuitive user interface. These design and user experience principles ensure that the user can interact with the machine easily and that the results are displayed in a clear and understandable way. Our aim is to enhance the overall user experience and engagement with the ancient divination practice.

Prototype/Outcome

CoinMind builds on existing work in coin-tossing divination rituals, such as the I Ching and the Tarot. The use of technology for divination and self-discovery also influenced the development of the CoinMind prototype. Below is a working prototype of a prediction machine that combines traditional divination practices with modern design and human-computer interaction concepts. 

First is our prototype diagram. As seen in the diagram, CoinMind underwent a series of design iterations to arrive at its current state. Initially, we brainstormed three different approaches to the first step of the prediction process, which is inputting the coin-toss result. However, after conducting several experiments, we ultimately decided to involve the user directly by allowing them to toss the coins physically. This decision was made based on feedback from test users, who indicated that the physical act of tossing the coins added to the overall experience of using CoinMind.

To create the physical device, we used a combination of fabrication and electronics. The box was laser-cut from a white acrylic board and stuck together to create a sense of minimalism and futurism of technology. Two springs with a holder are added to the base of the box to create a mechanism for users to toss the coin. Inside the box, including an Arduino microcontroller（Arduino Nano BLE 33, and an Adafruit LCD screen. 

The user simply tosses the coin six times inside the box, with the left side of the box colored white to represent Yang and the right side colored black to represent Yin. The machine will analyze the results of the coin tosses and provides insights into the user's future based on the hexagrams of the I Ching.

To determine the outcome of the coin toss, we used Arduino Nano BLE 33 to analyze the result of coin tosses by using its built-in microphone to distinguish the two different sounds of the coin falling onto either the left or right side of the box. We trained a machine learning model in Edge-Impulse, using two series of sound data corresponding to the coin falling onto the two sides of the boxes and a series of sound data of noises, as shown below. This approach ensured that the CoinMind machine accurately predicted the outcome of each coin toss.

Once the machine detects six results, it will generate the prediction result on the Adafruit LCD screen based on I Ching and the Bagua hexagram. An image of the fortune will occur on the LCD screen, followed by a paragraph of text explaining the content of the image, which is your fortune. There will be 64 different results of the whole system in total.

We acknowledge the contributions of prior work in these areas and seek further to explore the intersection of traditional wisdom and modern technology. A concept video of CoinMind in operation is below, along with detailed code.

Open Questions and Next Steps: 

While CoinMind is a functional prototype, there are still some unresolved issues that need to be addressed for future explorations. One area of concern is the accuracy of the machine learning model used to determine the outcome of the coin toss. While we have trained the model using sound data, though we already made a set of data of noise, there may be other factors that influence the outcome that we have not yet considered. Also, there may still be variations in how users toss the coins that could affect the outcome. In future explorations, it would be important to continue refining the machine learning model and testing it with different user groups to ensure that the predictions are as accurate as possible. Another question raised by this project is the potential spookiness of technology that seeks to predict the future. While divination practices have been used for centuries, the incorporation of machine learning and technology into these practices raises questions about how people perceive the role of technology in their spiritual and personal lives. These questions remain to be addressed as technology continues to play a larger role in our daily lives.

Reflection

Overall, the project successfully achieved its aspirations, but there is always room for growth and improvement in future iterations. We view the CoinMind project as a successful exploration of how traditional wisdom and modern technology can be combined to create an engaging and interactive experience for users. The use of machine learning to predict the results of coin-tossing divination rituals and the incorporation of principles of design and user experience in the physical design of the device make it a unique and innovative project. 

However, there is room for improvement. For example, in terms of sustainability, we may consider using recycled materials in the fabrication of the device. Also, to improve data accuracy in the CoinMind project, more diverse sound data of the coin falling onto different surfaces could be collected and used to train the machine learning model in Edge Impulse. Additionally, more precise data labeling and the use of data augmentation techniques could be explored. Furthermore, we may dig into conducting further research to explore the ethical implications of using machine learning in divination practices and the potential cultural appropriation of traditional divination systems. 

Attribution and References: 

- Edge-Impulse + Arduino Nano BLE 33 

https://docs.edgeimpulse.com/docs/development-platforms/officially-supported-mcu-targets/arduino-nano-33-ble-sense

https://docs.arduino.cc/tutorials/nano-33-ble-sense/edge-impulse

- How to use the I Ching to divine trigrams (Chinese)

https://www.sohu.com/a/304452653_100242598

- Use coins to make predictions based on I Ching and Bagua Diagram(Chinese)

https://www.bilibili.com/read/cv8853733?from=search

- I Ching Dataset

https://github.com/adamblvck/iching-wilhelm-dataset