Data Analytics for Healthy Food in the Cloud 2018-02-23T11:31:16+00:00

Data Analytics for Healthy Food in the Cloud

Drago Zagar & Goran Martinovic


Keywords: cloud computing; data analysis; food; health; mobile and web applications

H2020 challenge: Health, demographic change and wellbeing

Knowledge and skills (P: prerequisite; D: desirable, but not necessary): mobile and/or web application programming (P); data analysis (P); cloud computing (D); big data (D); basics of entrepreneurship (D)

With too little physical activity, stress and other factors, an unhealthy diet significantly affects a large number of people contracting chronic and other current diseases (e.g., diabetes, cardiovascular diseases, neurological disorders or metabolic syndromes), as in [1], [2]. Mobile and web technologies enable entry and collection of data on people’s condition and needs, while portable devices and sensors can be used as a source of valuable data that can facilitate planning a healthier diet adjusted to the diagnosis, condition and symptoms of a patient or a user with a certain level of risk of developing a disease [3], [4]. The analysis of the input and collected data should enable preparation of a nutrition profile of the user, planning, adjusting and monitoring eating habits and nutritional options, as in [5], [6]. On the other hand, the cloud provides infrastructure, computing, development/platform and analytical capabilities for developing a balanced diet system, as in [6], [7]. At day, week, and month levels, your start-up company should be able to suggest healthy food, give recommendations for its consumption, find places that sell healthy food, and avoid or warn of places selling unhealthy food. As in [8], [9], based on the principle of machine learning from the data, your company should also enable self-monitoring of patients’ condition and follow-up by a physician and/or a nutritionist.

[1] A. Abbas, et al. “Personalized healthcare cloud services for disease risk assessment and wellness management using social media,” Pervasive and Mobile Computing, vol. 28, pp. 81-99, June 2016.

[2] V. Apaolaza, et al. “Eat organic – Feel good? The relationship between organic food consumption, health concern and subjective wellbeing,” Food Quality and Preference, vol. 63, pp. 51.62, Jan. 2018.

[3] V. Kumari Yeruva, S. Junaid, Y. Lee. “Exploring social contextual influences on healthy eating using big data analytics,” in 2017 IEEE Int. Conf. on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, USA, 2017, pp. 1507-1514.

[4] C.-H. Wu, C.-H. Hung, J.-C. Ke. Analysis techniques of food nutrient data,” in Proc. ASE Big Data & Social Informatics 2015 (ASE BD&SI 2015), Kaohsiung, Taiwan, 2015, Article No. 11.

[5]F.M. Shiddieq, R. Kastaman, I. Ardiansah. “Development of people food consumption patterns information system based on web mobile application,” 2015 3rd Int. Conf. Adaptive and Intelligent Agroindustry (ICAIA), 3-4 Aug. 2015, pp. 267-273.

[6] Big data and analytics, [Online]. Available:

[7] M.M. Al-Jefri, et al. Using machine learning for automatic identification of evidence-based health information on the web,”, in 2017 Int. Conf. on Digital Health (DH ’17), London, UK, 2017, pp. 167-174.

[8] D. Ntalaperas, et al. “DISYS: an intelligent system for personalized nutritional recommendations in restaurants,” in 19th Panhellenic Conf. on Informatics, Athens, Greece, 2015, pp 382-387.

[9] S. Wolfert, L. Ge, C. Verdouw, M.-J. Bogaardt. Big data in smart farming – a review,” Agricultural Systems, vol. 153 pp. 69-80, May 2017.

Data analytics in changes of nutrition habits
Data analytics in changes of nutrition habits
The main challenges of data analytics in relation to healthy food
The main challenges of data analytics in relation to healthy food

Questions that need answers

  • Find and define sources, formats and content of data sets that can be used to identify symptoms and needs, and define dietary requirements of users depending on their habits.
  • Model, design (and optionally develop a proof-of-concept of) a web and mobile solution for data entry, collection and storage in a database, and for generating a plan, advice, and offer of healthy food. Fine-tune the interface from the point of view of user experience to the needs of users that need to adjust their eating habits.
  • Select and adjust data analysis procedures suitable for creating a diet plan, generating advice and warnings, and displaying offers referring to providing healthy food.
  • Based on the nature and symptoms of a disease or risky eating behaviours as well as requirements for adapted nutrition and possibilities of finding healthy food offers, identify target groups and specific user requirements of users from the point of view of the patient, users with risky eating behaviours, doctors, nutritionists and food providers.
  • Define channels aimed at including the target groups into the company IT system, and a customer relationship model that should allow users to adjust the IT system to the user’s requirements based on data analysis results.
  • Develop a model of financial sustainability and profitability for your start-up company based on the ability to promote and offer healthy food through advertising, social networks and web shops.
  • Evaluate, define and incorporate into your start-up company ways of how healthy eating planning will positively influence other aspects of healthy and interesting lifestyles, such as sport, health, tourism, and entertainment.
  • Explain ways and benefits of raising awareness of healthy eating and its impact on the health of individuals and society and use them to improve your company’s services and/or products through the model of cooperative learning.
  • Develop a healthy eating support system and encourage its impact on the production of healthy and environmentally friendly food.

Technical Expert

Drago Zagar does not have a photo :(

Drago Zagar


Goran Martinovic does not have a photo :(

Goran Martinovic


Business Expert

Rebeka Belavic does not have a photo :(

Rebeka Belavic


Societal Expert

Ignac Lovrek does not have a photo :(

Ignac Lovrek

Steering Committee Member, Lecturer

Case study students (Group 1)

Juraj Mihalov does not have a photo :(

Juraj Mihalov

TeamSoc21 Zagreb2018 Student

Desislava Nikolova does not have a photo :(

Desislava Nikolova

TeamSoc21 Zagreb2018 Student

Tima Redzovic does not have a photo :(

Tima Redzovic

TeamSoc21 Zagreb2018 Student

Filip Cesnek does not have a photo :(

Filip Cesnek

TeamSoc21 Zagreb2018 Student

Case study students (Group 2)

Attila Bagossy does not have a photo :(

Attila Bagossy

TeamSoc21 Zagreb2018 Student

Khaled Sherif does not have a photo :(

Khaled Sherif

TeamSoc21 Zagreb2018 Student

Victor Nacher Castellet does not have a photo :(

Victor Nacher Castellet

TeamSoc21 Zagreb2018 Student

Olga Chovancova does not have a photo :(

Olga Chovancova

TeamSoc21 Zagreb2018 Student

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