Digital agriculture for small-scale producers: challenges and opportunities Page 1 DECEMBER
2021 | VOL. 64 | NO. 12 | COMMUNICATIONS OF THE ACM 75 Digital Agriculture for …

The machine learning (ML) paradigm has gained much popularity today. Its algorithmic
models are employed in every field, such as natural language processing, pattern …

Smart sensors are useful in professional farming approach by which one can use the digital
technology to monitor, visualize, generate digital data, to control the application of …

Artificial intelligence for social good (AI4SG) is a research theme that aims to use and
advance artificial intelligence to address societal issues and improve the well-being of the …

As rocket launch cadences increase, access to space rises dramatically-setting the stage for
the next space industry surge. New, smaller, and less expensive satellites-now" …

More than two billion people globally live in smallholder farming households, comprising a
large proportion of the world's poor. Smallholder farm yields are estimated to reach only 25 …

The world needs to sustainably grow more food to feed the growing population of the planet.
Data-driven agriculture is a promising technique that can help farmers be more productive …

In recent years, reinforcement learning has achieved excellent results in low-dimensional
static action spaces such as games and simple robotics. However, the action space is …

Fast and accurate obstacle avoidance is crucial to drone safety. Yet existing on-board
sensor modules such as frame cameras and radars are ill-suited for doing so due to their …

Artificial intelligence (AI) provides many opportunities for social and economic
empowerment in developing countries. However, when one thinks of Africa, robotics does …