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Undernourishment Tracking
Undernourishment Tracking
Case Study

Undernourishment Tracking

Writer

Alex Turner

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WONG SZE FEI @ stock.adobe.com

In times of crisis, information is vital to save lives. Augmented Reality, combined with a small 3D infrared sensor, could automatically detect malnutrition in children through a simple scanning process using a mobile app.
In times of crisis, information is vital to save lives. Augmented Reality, combined with a small 3D infrared sensor, could automatically detect malnutrition in children through a simple scanning process using a mobile app.

With many nations facing crisis-level hunger, millions of people require emergency aid. Undernourishment causes many harmful effects on overall health, especially regarding children's development. A myriad of factors like local conflicts, displacement and migration, and climate change are affecting diets worldwide, exacerbating undernourishment levels.

In moments of crisis, information is vital to save lives. Usually, emergency aid requires fast solutions to provide timely, actionable food security, and nutrition analysis. Emerging technologies may offer more suitable tools to identify food insecurity and malnourishment to react in time and prevent these types of situations.

Hyperspectral Sensor Imaging (HSI), could automatically detect malnutrition in children through a simple scanning process using a mobile app. An example of this is Welthungerhilfe's Child Growth Monitor. Also, while HSI provides precise body measurements, 3D Modeling allows an algorithm to derive the nutritional status of an individual, and then record this data on a cloud-based platform, freeing field workers from this time-consuming process.

Future Perspectives

By gathering data collected from diagnosis to create patterns of repetitive behaviors of specific areas through Machine Learning Data Analytics, and, combined with Remote Sensing data, the tracking of undernourishment could also predict which places are suffering more from food insecurity issues. This innovative framework could create a whole map of nutritional difficulties worldwide and help decision-makers tackle solutions to improve global health. It could support better practices in the worst areas, such as ones impacted by climate change and unsettled economic conditions.

Currently, researchers are collecting data, both manually and digitally, to make AI models more accurate. However, despite the benefits of rapid response to aid in crises, technologies that gather personal data from citizens must be extremely secure: Data Enclaves could protect against potential privacy breaches of data collected from people in vulnerable populations fleeing hostile state governments.

7 topics
Education
Food and Nutrition Security
Global Health
Human Rights
Social Protection Systems
Universal Health Coverage
Youth and Sport
3 SDGs
02 Zero Hunger
03 Good Health and Well-Being
10 Reduce inequalities

Related Content

1 organizations
4 technology domains
3 technology methods
  • Hyperspectral Imaging (HSI)
  • 3D Modeling
  • Remote Sensing Data
2 technology applications
5 industries
  • Communications
  • Education
  • Food
  • Healthcare
  • Government & Citizenship
7 topics
  • Education
  • Food and Nutrition Security
  • Global Health
  • Human Rights
  • Social Protection Systems
  • Universal Health Coverage
  • Youth and Sport
3 SDGs
  • 02 Zero Hunger
  • 03 Good Health and Well-Being
  • 10 Reduce inequalities