- Bare Metal
- Bare Metal Cloud
- Big Data Benchmarks
- Big Data Experts Interviews
- Big Data Technologies
- Big Data Use Cases
- Big Data Week
- Data Lake as a Service
- Dedicated Servers
- Disaster Recovery
- GoTech World
- Industry Standards
- Online Retail
- People of Bigstep
- Performance for Big Data Apps
- Press Corner
- Tech Trends
- What is Big Data
How Big Data is Helping to Take a Bite Out of World Hunger
In a world with 7 billion souls, two-thirds of them go hungry on a regular basis. This is in spite of the fact that about 30 percent of the food the world produces actually goes to waste. As we barrel through the second decade of the 21st century, this simply won't do.
In a world with 7 billion souls, two-thirds of them go hungry on a regular basis. This is in spite of the fact that about 30 percent of the food the world produces actually goes to waste. As we barrel through the second decade of the 21st century, this simply won’t do.
Big Data Has an App for That
Fortunately, this represents one of the strengths of big data. Data and analytics can help solve problems just like this—finding real and workable solutions to real world problems. With the help of Apache Spark, one app developer is helping to put an end to world hunger, a problem that has plagued humankind throughout the modern era.
Food Cloud matches retailers that have food that might ordinarily go to waste with charities that have the means by which to transport the food, as well as connections with needy people who can use the food. There are already a few retailers and charities using the Food Cloud app, keeping almost 6 tons of nutritious foods out of landfills.
How Big Data Matches Surplus Food With People in Need
According to Food Cloud developers, the retailer that has food to donate scans the food items and uses the app to designate it as something for donation. The app distributes this information to charities that have a need for food. The charities then schedule to pick up the food and deliver it to needy people before the food goes to waste.
This method also uses big data to detect instantly if there is a problem in the system so that it can be fixed, meaning less food goes to waste and more hungry people get fed. For example, the big data analytics behind the app can detect when there are problems with the Internet connection of a retail donor or a participating charity, or determine when there are delivery problems that need to be solved.
This method of distribution means that the food remains traceable throughout the process of distribution. There is no time at which the food changes hands without being traced, which helps eliminate problems with food borne illnesses or feeding hungry people potentially harmful food. It also eliminates the potential for someone to deliberately do something nefarious with food donated to a charitable organization, as deplorable as that may be.
Big Data: Good for People, Good for the Environment
Not only is this an excellent humanitarian option, it’s a prime example of big data helping the environment. Growing, transporting, and keeping food at the optimal temperature all carry a significant carbon footprint. Using big data to keep it from going to waste means that more people can eat well without unnecessarily damaging the environment.
Before long, the Food Cloud app will be able to do even more to help keep good food out of dumpsters, as well as eliminate those environmentally unfriendly garbage truck trips to the landfills. Upcoming features include IoT sensors that will track the temperature of the food as it is stored and transported, as well as location trackers that would help retailer and the charities they donate to find the most efficient routes by which to transport the donated food.
Do you have a real world problem that can be solved by big data and data analytics? Don’t trust it to anything less than the world’s first Full Metal Data Lake. For a limited time only, you can discover the first Full Metal Data Lake as a Service in the world. Get 1TB free for life - limited to 100 applicants. Start here.