{"id":4019,"date":"2025-06-02T16:42:51","date_gmt":"2025-06-02T16:42:51","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2025\/06\/02\/researchers-and-students-in-turkiye-build-ai-robotics-tools-to-boost-disaster-readiness\/"},"modified":"2025-06-02T16:42:51","modified_gmt":"2025-06-02T16:42:51","slug":"researchers-and-students-in-turkiye-build-ai-robotics-tools-to-boost-disaster-readiness","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2025\/06\/02\/researchers-and-students-in-turkiye-build-ai-robotics-tools-to-boost-disaster-readiness\/","title":{"rendered":"Researchers and Students in T\u00fcrkiye Build AI, Robotics Tools to Boost Disaster Readiness"},"content":{"rendered":"
\n\t\t<\/span> <\/span> <\/span><\/span><\/p>\n

Since a 7.8-magnitude earthquake hit Syria and T\u00fcrkiye two years ago \u2014 leaving 55,000 people dead, 130,000 injured and millions displaced from their homes \u2014 students, researchers and developers have been harnessing the latest AI robotics technologies to increase disaster preparedness in the region.<\/p>\n

The work is part of a Disaster Response Innovation and Education Grant provided by NVIDIA in collaboration with Bridge to T\u00fcrkiye Fund<\/a>, a nonprofit supporting underserved communities in T\u00fcrkiye, with a focus on education and sustainability.<\/p>\n

The fruits of the grant \u2014 which provided 100 free NVIDIA Jetson Nano Developer Kits<\/a> and $50,000 in funding divided among eight awardees \u2014 are now being realized through projects on AI-powered inspection, search and rescue, robotics education and more.<\/p>\n

Recipients of the grant have, for example, trained robots on key skills needed in search-and-rescue operations, built a tool to test water and food sources for pathogen contamination in disaster-stricken areas, and launched a hands-on programming course at a Turkish institute of technology.<\/p>\n

The grant\u2019s impact is in addition to the more than $1.9 million in employee donations and company matching<\/a> provided by NVIDIANs around the globe to support victims of the devastating earthquakes.<\/p>\n

\u201cAfter the earthquake, we didn\u2019t want to be bystanders,\u201d said Harun Bayraktar, senior director of libraries engineering at NVIDIA. \u201cWe wanted to invest our time and efforts to make a difference and save lives next time.\u201d<\/p>\n

Bayraktar and Berra Kara, a senior GPU power architect at NVIDIA \u2014 both of whom grew up in T\u00fcrkiye \u2014 volunteered to lead the grant program team, aiming to raise awareness for disaster response in the country, increase AI and robotics expertise, and help minimize the casualties of any future earthquakes.<\/p>\n

Read more about the rippling impacts of NVIDIA and Bridge to T\u00fcrkiye\u2019s grant program:<\/p>\n

Researchers Build Unmanned Ground Vehicle for Search and Rescue<\/b><\/h2>\n

At Ankara University, in the country\u2019s capital, researchers used the grant to build a modular unmanned ground vehicle (UGV) that can support search-and-rescue operations in post-earthquake scenarios.<\/p>\n

Equipped with a thermal camera, an RGB-D camera and an NVIDIA Jetson Nano Developer Kit, the small, durable UGV scans environments in 3D and detects thermal activity, so users can determine the presence of a human in the aftermath of a disaster while maintaining a safe distance from dangerous areas.<\/p>\n

\u201cOur autonomous UGV system used the NVIDIA Jetson Nano\u2019s onboard AI computing power to perform real-time, thermal vision-based victim detection in post-disaster search-and-rescue scenarios,\u201d said Mehmet Cem \u00c7atalba\u015f, associate professor in the software engineering department at Ankara University. \u201cNVIDIA\u2019s earthquake relief program significantly accelerated our research and development process, transforming an innovative concept into an effective, life-saving solution.\u201d<\/p>\n

University Students Train Robots to Navigate Post-Disaster Environments<\/b><\/h2>\n

\"\"<\/p>\n

Simultaneous localization and mapping (SLAM<\/a>), a commonly used method to help robots map areas and find their way around unknown environments, is a critical skill for robots that could be used in search-and-rescue missions.<\/p>\n

To equip students with SLAM and other robotics skills, the computer engineering department at Hacettepe University \u2014 a world-class research university in Ankara \u2014 integrated NVIDIA Jetson Nano Developer Kit-based projects into two courses. More than a dozen students used the embedded AI developer kits to build small mobile robots, dubbed \u201cDuckiebots,\u201d with SLAM capabilities.<\/p>\n

Using SLAM, sensor integration and autonomous-navigation features, AI-powered robots like these could enter various areas \u2014 such as collapsed buildings or fires \u2014 to help find and rescue people.<\/p>\n

Through these courses, Hacettepe University students simulated potential planned paths for robots, as well as assembly and initial operation of the Duckiebots.<\/p>\n

Researchers Enable Fast Pathogen Screening in Disaster-Stricken Areas<\/b><\/h2>\n

In the aftermath of earthquakes, floods, wildfires and other natural disasters, a lack of sanitation and access to clean water can often lead to disease outbreaks. It\u2019s important to test water and food sources for pathogen contamination and quickly identify the types of any existing pathogens to prevent their spread.<\/p>\n

Researchers at Bilkent University, a nonprofit research university in Ankara, built a mini supercomputer cluster \u2014 based on the NVIDIA Jetson Nano Developer Kits \u2014 that promptly carries out computational tasks related to metagenomic analysis, or the analysis of DNA from a sample of an environment.<\/p>\n

\"\"<\/p>\n

The portability of the NVIDIA Jetson devices means the cluster can be easily transported to disaster-stricken areas to identify pathogens directly on site \u2014 rather than needing to send samples to a wet lab \u2014 helping to efficiently, speedily prevent disease spread.<\/p>\n

The research team used the open-source CuCLARK<\/a> library for metagenomic classification using NVIDIA CUDA<\/a>-enabled GPUs, which resulted in fast, accurate DNA screening.<\/p>\n

University Students Learn the Fundamentals of AI and Embedded Systems<\/b><\/h2>\n

\"\"At the Izmir Institute of Technology \u2014 a research university that places a strong emphasis on the natural sciences and engineering \u2014 the computer engineering department tapped into the NVIDIA Jetson Nano devices, CUDA and NVIDIA Deep Learning Institute<\/a> teaching kits to equip nearly 80 undergraduates with the fundamentals of AI, accelerated computing<\/a> and robotics.<\/p>\n

\u201cUsing the Jetson Nano Developer Kits provided by the NVIDIA and Bridge to T\u00fcrkiye grant, we expanded our heterogeneous parallel programming course to include a hands-on deep learning project for computer science undergraduates,\u201d said I\u015f\u0131l \u00d6z, assistant professor of computer engineering at the university. \u201cSuch hands-on experience makes learning more engaging and effective for the next generation of innovators who will help build life-saving, sustainable technologies.\u201d<\/p>\n

Based on this work, a paper titled, \u201cTeaching Accelerated Computing With Hands-on Experience<\/a>,\u201d will be presented by \u00d6z at this month\u2019s IEEE International Parallel and Distributed Processing Symposium. The paper outlines the challenges and successes that come with teaching heterogeneous parallel programming \u2014 a type of computing that uses more than one kind of processor or core to increase performance and energy efficiency.<\/p>\n

Learn about the <\/i>NVIDIA Academic Grant Program<\/i><\/a>.<\/i><\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

https:\/\/blogs.nvidia.com\/blog\/turkiye-disaster-readiness-ai-robotics\/<\/p>\n","protected":false},"author":0,"featured_media":4020,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/4019"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=4019"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/4019\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/4020"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=4019"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=4019"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=4019"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}