Geospatial artificial intelligence: the technology standing on the shoulders of giants

人工智能(AI)和地理/地理信息系统(地理信息系统)维度的结合创造了地理空间人工智能(GEOAI)。Not just the technologies powering your Uber,there is an emerging role for GeoAI in health and healthcare as location is an integral part of both population and individual health.In aneditorialrecently published in国际卫生地理杂志,Maged N.Kamel Boulos及其同事讨论公共卫生和智能城市的人口水平geoai应用,and integration of GeoAI into precision medicine.

Nanos gigantum humeris insidentes.GeoAI is ‘standing on the shoulders of giants',即人工智能/深度学习和地理信息系统技术。

协同汇流artificial intelligence(AI,especially ‘deep learning‘,一种类型的machine learning)以及地理位置/地理信息系统dimension creates GeoAI.后者是一个常用的术语,指的是一组比其父组件(ai+gis)总和强大得多的技术。

GeoAI opens up big opportunities and applications in health and healthcare,因为地理位置对人口和个人健康都起着关键作用。

GeoAI opens up big opportunities and applications in health and healthcare,因为地理位置对人口和个人健康都起着关键作用。公共卫生领域的几个学科,,精密医学,andIoT (Internet of Things)-powered ‘smart healthy cities and regions‘ are benefiting from GeoAI,e.g.,environmental health,epidemiology,genetics and epigenetics,social and behavioral sciences,传染病,to name but a few.

Geo-tagged big data collated from rich sources,such associal mediastreams,satellite imagery (remote sensing),,智能城市的物联网传感器(e.g.,monitoring air,light,and sound pollution),and personal sensing (via connected ambient and wearable sensors),can be reasoned with using GeoAI to answer many important research and practice questions in more comprehensive ways.

GeoAI technologies can capture and model our environment,把我们住的地方联系起来,work,travel,and spend our time to environmental,social,and other types of location-specific exposures,to explore their potential role(s) in influencing our health.它们也可以产生新的假设,predict disease occurrence,and help plan and monitor the deployment of effective health promotion and disease prevention and control programs within smart healthy cities.Besides these population-level GeoAI applications,there are further opportunities for integration of GeoAI and定位信息智能转化为精确医学via well-tailored mHealth (mobile health) interventions targeting individual patients.

GeoAI applications and possibilities are not just the product of technological advances in recent years.吉爱站在巨人的肩膀上,' namely AI/deep learning and GIS technologies.

All of the above GeoAI applications and possibilities are not just the product of technological advances in recent years.GeoAI是standing on the shoulders of giants‘ (Latin:肱骨内纳米巨人),即人工智能/深度学习和地理信息系统技术。这些巨人花费了许多科学家和学者(常常被遗忘)几十年的辛勤劳动来发展和成熟到他们目前的形式。

For example,as many of us already know,deep learning is not a new term or an invention of the last several years.Deep learning was introduced to the machine learning communityin 1986 by Rina Dechter,计算机科学家,并且artificial neural networksin 2000 by艾森伯格,also a computer scientist et al.,decades before being brought to public attention in mainstream news media by Google afterthey bought the British start-up DeepMind in 2014.Aizenberg and colleagues were in turn building on the output of generations of scientists before them,including the first mathematical model of a neural network developed in 1943 byWalter H PittsJr,a logician,andWarren S McCulloch,神经科学家

Similarly,,the field of GIS traces its roots back to the 1960sand even在50年代之前,多亏了瓦尔多·R·托布勒,地理学家和制图师,who in 1959 conceived MIMO (map in,地图)a model for computer cartography,andRoger F Tomlinson,OC,a geographer and the ‘father of GIS'.

Let's always remember those before us who have laid the foundations for our present day and future innovations.

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