Innovate to Eradicate Hunger: Unveiling 8 Tech Innovations Accelerating for Impact
Meet the 8 teams anchored in technological innovation selected to take part in the new ‘World Food Programme (WFP) Humanitarian Ventures Accelerator’ programme with the WFP Innovation Accelerator.
By Lucy Bloxham
In 2024, the world continues to face unprecedented challenges. Global hunger is soaring, and the contributing factors — conflict, climate change and the rising cost of living — seem only to be increasing in frequency and severity. Overcoming these challenges will take innovation, technology, revolutionary ideas and the right partner to bring those ideas to bear. Building on a history of collaboration, Google.org has made a US$2.8 million grant to World Food Program USA in support of the WFP Innovation Accelerator. With this grant, the WFP Innovation Accelerator and Google for Startups are embarking on a journey of innovation and disruption to accelerate achieving the Sustainable Development Goals.
Google for Startups and the WFP Innovation Accelerator have co-designed an acceleration programme, the World Food Programme Humanitarian Ventures Accelerator, that kicks off this month to advance and scale eight ventures created and developed within WFP. These innovations, which leverage Artificial Intelligence (AI), machine learning, cloud computing and data analytics technologies, focus on improving emergency response, supply chain efficiency and support for smallholder farmers. Throughout the programme, the chosen teams will work closely with WFP Innovation Accelerator innovation consultants and Google for Startups mentors and technical success managers to progressively build their solutions and scale their impact.
Unified in purpose, the WFP Innovation Accelerator, Google for Startups, and the participating ventures aim to amplify the scalability of humanitarian innovation. Explore the profiles of the participating teams below and delve into their groundbreaking solutions as they gear up to accelerate for a meaningful impact.
Given the many crises we currently face in global humanitarian operations, WFP’s role is critical in responding to emergencies and delivering assistance to those in need. To effectively respond to these crises, WFP must innovate to make a greater impact with limited resources.
Climate-related, political, or economic crises can severely impact local economies and food security. Rapid and accurate data collection is essential for effective response, but often hindered by time, physical, and financial constraints.
The Shock and Assistance Platform for Economic Simulations (SHAPES) addresses this by analysing affected regions to estimate the number of people requiring aid and suggesting the most effective assistance methods. Accessible through a user-friendly web platform, SHAPES enables WFP Country Offices to customize scenarios involving various shocks (like extreme weather or economic inflation) and assistance strategies (such as cash transfers).
SHAPES has significantly reduced emergency assessment times from six months to three, saving up to US$200,000 per analysis. It has been instrumental in strategizing for countries like Afghanistan, Yemen, Ethiopia, and Haiti. With a goal to expand globally to 120 countries, SHAPES aims to support over 150 million people by 2026, demonstrating its substantial impact and potential in global crisis management.
Geographic targeting is the most common method to identify areas and populations in most need of assistance. Staff in WFP Country Offices are often responsible for conducting targeting, but can lack high-quality, up-to-date, and detailed data. This makes geographic targeting imprecise and may exclude vulnerable communities.
GeoTar is a user-friendly geospatial vulnerability profiling and targeting tool for decision-makers. Taking into account climate change, agricultural capacity, service utilization and access, GeoTar creates detailed vulnerability maps. This enhances operational decisions in WFP Country Offices by reducing the need for manually collected household data, especially in places where such data is scarce and hard to collect. This results in a 30 percent increase in targeting accuracy and savings of US$300,000 for each country using it. When scaling GeoTar, the team plans to include multidimensional drone data, which will improve information precision. GeoTar is currently implemented in Iraq, Chad, and Colombia and plans to expand to Afghanistan, Somalia, Venezuela, and Bangladesh. The team aims to save up to US$9 million each year on targeting.
In times of crisis, effective communication is vital for humanitarian organizations to understand the needs, concerns and behaviours of affected populations. However, conventional communication methods can sometimes lead to restricted insights and impede targeted assistance and emergency preparedness initiatives. The ETC Chatbot serves as a tool for people impacted by disasters. It helps them conveniently access up-to-date information about essential services and offers ongoing assistance when crises strike. It also helps collect critical data and coordinate emergency responses across various UN agencies. So far, the ETC Chatbot has supported over 100,000 vulnerable people, giving them access to life-saving information. Currently, the ETC Chatbot focuses on a specific national crisis context, for example in Ukraine, however there are plans to deploy the chatbot solution globally.
During emergencies, telecommunications networks are often destroyed, resulting in connectivity issues. This can make humanitarian response coordination difficult, leading to delays in coordinating search and rescue operations and creating inefficiencies in the distribution of critical supplies.
The Rapid Response Connectivity Carrier (R2C2) is a 90-metre communications tower and tethered drone that improves coordination of emergency response by enhancing real-time communication. A cable runs between the tower and a LTE (4G) transmitter drone that flies 24 hours a day, covering a three square kilometre area and providing thousands of affected people and humanitarian responders with internet access. R2C2 has the potential to reduce rescue times by 3 hours per mission, which can add up to 105 hours in typical emergency scenarios. It is currently being tested in Tanzania and Mozambique. The innovation also has the potential to scale its operations to densely populated areas, reaching up to 5 million people.
Machine learning for drought seasonal forecast and anticipatory action
The impact of climate change is worsening the food insecurity of small-scale farmers. This situation is exacerbated by the less-than-ideal warning systems and the limitations of the current methods for predicting seasonal weather.
Machine learning for anticipatory actions takes a proactive approach to dealing with drought risks, using cutting-edge data analysis and insights from climate experts. This solution uses AI and machine learning to improve predictions of weather risks for vulnerable people, allowing for quick warnings and timely help. The team comprises data scientists, a climate risk and anticipatory action specialist, and an earth observation data analyst, each with strong WFP operational expertise. So far, machine learning using this method has supported 550,000 people with anticipatory emergency cash-based transfer assistance in Zimbabwe, Mozambique, Tanzania, Malawi and Jordan.
The team plans to expand geographic coverage across southern Africa, accommodating different climate hazards. This can save up to US$100 million in losses due to climate change.
Cash-based transfers give people the freedom to meet essential needs as they choose, stimulating local economies and enabling financial inclusion. Cash-based transfers now account for 35 percent of WFP’s assistance.
In 2022, WFP distributed a historic US$3.26 billion in cash assistance across 72 countries. However, challenges persist in ensuring all recipients receive funds. Such obstacles include limited digital infrastructure, low data literacy, and the diversity of systems used by partners.
DARTs (Data Assurance and Reconciliation Tool Simplified) is a user-friendly web app backed up by sophisticated machine learning modules. This system enables WFP to implement controls on large cash transfer data and eases the process of comparing transactions and activity, which is vital in cash assistance programmes. It ensures that cash assistance is accurate and precise, promotes WFP’s accountability to its donors, assesses programme efficiency and builds trust across WFP operations.
So far, DARTs has reached more than 1.1 million people, increased operational efficiency ninefold and assured around US$1 million. It also has scaled to five countries — The Gambia, Guinea, Iran, Senegal, and Sierra Leone — in less than a year.
Strong supply chains play a critical role for humanitarian organizations because they ensure the efficient and timely delivery of essential goods and services to those in need during emergencies or crises.
Route the Meals
Delivering food efficiently to diverse, remote areas with varying constraints poses challenges, which means it can be difficult to deliver school meal assistance to every school in certain locations where WFP operates. Each country has unique logistical hurdles impacting food distribution effectiveness.
Route The Meals applies mathematical models to simplify and improve the planning of delivery paths and warehouse placements. Using such models, Route The Meals aims to shorten delivery times, reduce transport costs and decrease the environmental footprint of food deliveries in order to ensure that food reaches schools, even in far-off places, more efficiently. So far, Route the Meal has been implemented in Haiti and Benin, serving 1.7 million children. Since its implementation, it has reduced travel distance and the total lead time for food to travel from warehouse to school, resulting in cost savings of about US$375,000.
By the end of 2025, the Route the Meal team aims to support 22 million children and expand its reach to additional WFP core programmes.
Management services are crucial for humanitarian organizations because they provide the framework and expertise needed to ensure that resources are effectively utilized.
UN AI Mobility
Securing transportation and accommodation in a city is a straightforward task. However, when attempting to do so in remote field areas where WFP operates, it becomes much more complex. The UN Booking Hub, managed by WFP, is a worldwide single platform resource for many UN agencies. It streamlines critical travel and lodging services, including guesthouses, UN aircraft, and UN vehicles. This tool ensures the safe movement of international humanitarian groups when on emergency missions. So far, it has supported 2.5 million global humanitarian communities.
However, it currently has a complicated manual system for assigning resources. This adds another layer of complexity to the challenging humanitarian context. Without powerful machine learning, there’s a missed chance to save costs and allocate the budget effectively.
The team aims to double the user reach in the next two years and reduce WFP’s CO2 footprint by 10 million per year.
The WFP Innovation Accelerator sources, supports and scales high-potential solutions to end hunger worldwide. We provide WFP staff, entrepreneurs, start-ups, companies and non-governmental organizations with access to funding, mentorship, hands-on support and WFP operations.