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Fighting World Hunger

Learn about the advantages of adopting new technologies like AI in the agricultural industry

This research focused on testing with maize, economical crop grown in Phetchabun province, Thailand, by installing a total of 20 sets of internet of things (IoT) devices which consist of soil moisture sensors and temperature and humidity sensors (DHT11). Data science tools such as rapidminer studio was used for data cleansing, data imputation, clustering, and prediction. Next, these data would undergo data cleansing in order to group them to obtain optimization clustering to identify the optimum condition and amount of water required to grow the maize through k-mean technique. From the analysis, the optimization result showed 3 classes and these data were further analyzed through prediction to identify precision. By comparing several algorithms including artificial neural network (ANN), decision tree, naïve bayes, and deep learning, it was found that deep learning algorithm can provide the most accurate result at 99.6% with root mean square error (RMSE)=0.0039. The algorithm obtained was used to write function to control the automated watering system to make sure that the temperature and humidity for growing maize is at appropriate condition. By using the improved watering system, it improved the efficacy of watering system which saves more water by 13.89%.

Artificial Intelligence (AI) can revolutionize agriculture which impacts a country’s economy, employing more than 30% of the world’s population directly or indirectly. It can fulfill the needs of an ever-growing world’s population through automation. Traditional farmland practices like weeding, pesticide spraying, irrigation, monitoring soil nutritional and moisture status, etc. can be performed quicker using robots, sensors, drones, and algorithms. It reduces water wastage and pesticide overuse, maintains soil fertility, helps in reducing labor and enhances crop yield and productivity despite world problems. However, its penetration into agriculture is still in its infancy due to its uneconomical nature, lack of expertise and big data requirement for accuracy among others. This paper delves deeper into the various applications and impacts of AI in agriculture, new tools being used, challenges and future scope related to this field. Combined with Artificial Neural Network (ANN) models and Machine Learning (ML), along with Expert systems (ES) and Internet of Things (IoT), AI can do wonders in agriculture in the subsequent years to come.

Prime Minister Benjamin Netanyahu and Chinese Vice President Wang Qishan toured the innovation exhibit at which five Israeli companies presented their inventions in the fields of agriculture, medicine, smart transportation, advanced vision technology and artificial intelligence. https://t.co/uk8VOXdnp2 Source: https://twitter.com/IsraeliPM/status/1055155087033724928 Uploader: PM of Israel

Precision agriculture (PA) represents a modern farming approach that integrates advanced technologies to optimize crop production while minimizing environmental impact. This paper explores the role of artificial intelligence (AI) in enhancing precision agriculture by improving crop yields, reducing resource wastage, and promoting sustainable farming practices. AI techniques, such as machine learning, remote sensing, and robotics, are being increasingly utilized to monitor crop health, predict yields, and manage farm resources effectively. The paper discusses various applications of AI in agriculture, examines the challenges and opportunities in implementing AI-driven solutions, and highlights case studies that demonstrate the success of AI in precision agriculture. Future trends and innovations in AI technologies are also explored, providing insights into the potential of AI to revolutionize the agricultural sector

The way we feed ourselves is changing. Agriculture will also be impacted by Artificial Intelligence. Could AI present an opportunity for increased food security in the future? From the climate crisis to depleted soils: farmers all over the world fear for their future. Our food security is at risk. The United Nations wants to end hunger worldwide by 2030. The advent of Artificial Intelligence could help. In Cameroon, Adamou Nchange Kouotou has developed an AI-supported app that farmers can use to scan their crops. This enables them to recognize whether the plants are healthy, find out which pests are present and receive specific instructions for how to combat problems. This AI app already provides direct help to many small farmers who are cultivating depleted soils in the sub-Saharan region. In southern Spain, the vegetable garden of Europe, Joaquín Soriano Fernandez relies on sensors to maintain the right temperature and humidity levels in his greenhouses. An algorithm ensures that drought-stricken farmers in the region can irrigate more precisely - and thus save a lot of water. In Madrid, engineer Roemi Fernandez Saavedra is researching new harvesting technologies. Her two-armed harvesting robot can already recognize the shape of ripe tomatoes and eggplants. Her aim is to reduce costs and waste, while freeing people from undignified working conditions. One of the biggest problems we face is food waste. In Germany alone, eleven million tons of food end up in the bin every year. 17 percent of this is produced in restaurants and canteens. That is why a company canteen in Lünen is now using an AI forecasting system that predicts which dishes are most likely to be in demand during the lunch break. Ethical issues are a major hurdle when using AI. Ameca, the world's most advanced humanoid robot, guides us through the film with his assessments: What are the potentials and limits of AI?

Fighting World Hunger

Fighting World Hunger

Perma.cc archive of https://www.marketsandmarkets.com/Market-Reports/ai-in-agriculture-market-159957009.html created on 2022-02-14 01:46:16.494662+00:00.

Fighting World Hunger

Fighting World Hunger

Fighting World Hunger

Fighting World Hunger

Fighting World Hunger

This rapid review aims to seeks to gather, assess, and synthesise the available evidence on the effectiveness and impact of AI-enabled solutions in agriculture. It also seeks to capture evidence that will help us to investigate how AI is defined in the agriculture sector, understand the types, sub-fields, position along the agricultural value chain, and stage of development of AI applications in agriculture. Moreover, the review seeks to capture ethics and equity considerations in AI applications to agriculture and allow us to comment on medium-, short- and long-term trajectories of specific AI applications. Overall, the review seeks to inform key investment decisions to build an effective, efficient and equitable landscape in AI.

Artificial Intelligence is one of the emerging technologies in the field of agriculture which tries to simulate human reasoning in intelligent systems. It is making a revolution in agriculture by replacing inefficient traditional methods with more efficient AI based methods. AI is used in agriculture in various ways such as automation, robots, drones, soil and crop monitoring, and predictive analytics. This paper provides various applications of AI tools in agriculture. Matthew N. O. Sadiku | Sarhan M. Musa | Abayomi Ajayi-Majebi "Artificial Intelligence in Agriculture" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38513.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/38513/artificial-intelligence-in-agriculture/matthew-n-o-sadiku