1. Explanation (problem background introduction)
In our busy daily life, housework has been an increasing hassle for young generations, especially housekeeping in our refrigerator. The food (fruit, meat, vegetables, etc) stored in the refrigerator can be easily forgotten at times and goes bad quickly, leading to food wastage. Besides, food wastage has been a common phenomenon around the world. Official data shows that in 2018, there has been 1.3 billion tons of food waste worldwide, which accounts for nearly one-third of total food production. Considering the demand on convenience in housekeeping and the food saving, developing some technology to help people to manage their refrigerator is necessary and prospective.
So the problem is, people want their refrigerator to sensor the information of food and alert them if the food go bad.
2. Guidelines for Students
The teacher will divide everyone into groups of 3-4 students each.
Each group shall do some basic research about the problem and brainstorm possible solutions, finally, choose the most desirable one.
After deciding on the chosen idea, the group shall find the necessary materials and make a prototype,test and instructions are desirable.
Finally, the group shall present the product and persuade others to buy it or invest it.
Processing mindset : how to think as an engineer and solve a problem systematically
Information searching: find relevant information from different sources
Technology skills ：how to make a prototype and explain how it works, including the basic concept and knowledge about engineering.
Teamwork skills: communicate with different people and collaborate together
Roadshow and pitch: how to show your product vividly and persuade others to buy your products or find investment for it.
1） Different solutions (25 points)
Search via Internet(google/baidu/bing), filter out outdated information, come up with your own solutions. Find relevant updated information and research results from databases offered by your institution.
Try to view the problem from different perspectives. If you were a user, which kind of solution would you buy, how much money would you spend on such product? If you were a product developer, would you like it to be very complicated and use many cutting-edge technologies, so that your potential competitors could not steal your idea?
Recommend to take every key factor leading to the success of your product into consideration. For instance, is it easy to use, is your solution straight forward and hitting the pain point?
2) Why you choose the solution (20 points)
3) Prototype (20 points)
What are the factors, demands, functions, or considerations it must have? How does it work? Will it be user-friendly for the customers?
4) Present and Persuasion (25 points)
Understand the target audience and how this product will meet their demands. Present the idea’s functionality and affordability, whether it is suitable and attractive enough for the audience. Describe the profit analysis, how the sales will generate revenue. Finally, how to persuade target audience and others to buy it.
5) Bonus (Up to 20 points)
Market research: whether the group has done market research and do cost control
Appearance: whether the product is user-friendly and attractive
Video: whether the video can describe the product clearly and interesting enough.
Here is an example of ours.
We got a bar code scanner for packaged food. And a camera for homemade food and food without wrappers. There is an input button to trigger the input event, which write records to the inner database. And an output button to switch mode, to delete records. There are two buttons for different mode, system default mode or manual mode, which enables the flexibility to change the expire date of certain food.
> One-click identification for Wi-Fi
> Scanning when food in and out
> Automatic alerting by email
2> Integrated Design
Casalinuovo, I., Di Pierro, D., Coletta, M. and Di Francesco, P., 2006. Application of electronic noses for disease diagnosis and food spoilage detection. Sensors, 6(11), pp.1428-1439.
Ellis, D.I., Broadhurst, D., Kell, D.B., Rowland, J.J. and Goodacre, R., 2002. Rapid and quantitative detection of the microbial spoilage of meat by Fourier transform infrared spectroscopy and machine learning. Appl. Environ. Microbiol., 68(6), pp.2822-2828.