Ending global hunger has long been a critical goal for the global community. When the United Nations鈥 Sustainable Development Goals were released in 2014, ending hunger, food insecurity and all forms of malnutrition formed SDG2.
Though there has been some progress in the fight against hunger 鈥撀爋ngoing conflicts, climate change, economic downturns and the COVID-19 pandemic have been major barriers to achieving SDG2. As of 2020, according to the UN, 720 and 811 million people globally faced hunger, and current estimates suggest that 660 million people may still face hunger in 2030.聽
Professor Salah Sukkarieh,聽a robotics engineer at the University of Sydney鈥檚聽Australian Centre for Field Robotics, will this week speak at the United Nations Food and Agriculture Organization鈥檚 (FAO)聽聽in Rome (2-4 November).
Co-chairing the conference's Mechanization and Digitalization session, he will discuss how agricultural robotics and AI can support nutrition security and increase productivity and yields, drawing on his team's development of autonomous agricultural robots that have been designed to improve food security in the Asia-Pacific.
The team has developed Digital Farmhand, a small, autonomous, electric tractor-like vehicle can assist smallholder farmers to improve their productivity and yields.
鈥淚t鈥檚 projected that APAC will need to increase food production by up to 77 percent to feed its communities by 2050. Bold steps must be taken to accelerate progress towards addressing the major drivers of food insecurity, malnutrition, and equal access to food 鈥撀燼s well as drive smart solutions that give back power to local farmers,鈥 said Professor Sukkarieh.聽
Digital Farmhand. Australian Centre for Field Robotics.
鈥淥ur Digital Farmhand robot is designed to assist smallholder farmers to improve their productivity and yields and, ultimately, provide a more reliable income amidst changing markets and climates. In its simplest form the Digital Farmhand is a small, autonomous electric tractor-like vehicle that can tow a variety of implements such as seeders, weeders and bed preparation tools, and can undertake precision automation of many labour-intensive farm tasks, like weeding, spraying and seeding.鈥
鈥淒igital Farmhand can also use accessible smartphone technologies along with AI to provide crop analytics such as yield estimation or pest and disease identification.鈥
Professor Sukkarieh鈥檚 team is looking to build a localised, modular version of Digital Farmhand using materials that can be readily sourced within the APAC region, including electric/petrol scooter parts, making maintenance easier for communities. They are also developing open-source artificial intelligence packages for smartphones which can be easily accessed in the APAC.聽
鈥淥ur studies and fieldwork have found that the issues concerning smallholder farmers in the APAC are no different to those in Australia, so we believe the technology can provide the same benefits. However, it is the economics of introducing the technology that requires different solutions.鈥