People are dependent on food. Various nutrients such as water, carbohydrates, protein or similar serve to enable humans to perform various functions. But not only the intake itself is important, but also when and where. At work the consumption of food is very underestimated. We are so busy every day that we even forget to eat. This has an effect on our health, influences productivity and prevents us from achieving our goals.

Stress and eating at the workplace are harmful to health and can lead to separation from the community. lunch-bot helps to prevent these problems by simplifying collaborative food planning. The key elements of lunch-bot are organisation, inspiration and bringing people together.

Eating together promotes the corporate community. It also provides a balance and a more conscious break. It also helps to get to know other food cultures instead of sticking to ones own eating habits. We took several personalities and example scenarios into account to conceptualise the character and functionality of lunch-bot.

The solution is to plan lunch together in the working environment: order food, go out to eat or cook together. Our attentive bot actively responds to our users and reports though light and sound or directly in a chat. He also collects donations to finance cooking together.

In future scenarios, it gets even more adaptive, when lunch-bot can focus on personalities individually by implementing machine learning: Whether the user has certain preferences so that he can offer the user variety. The bot also knows exactly when to leave the user alone, or can give more emphasis or inspiration.