In this rapid reshaping of the world through artificially replicated human intelligence by computer systems, it can be quite difficult to keep up. Artificial Intelligence has been creating impressive advancements in almost every sector like Agriculture, Supply management, Education, business, and so on.
Let us explore some Artificial Intelligence technologies that you should know.
It is expected that the global market size for ‘smart agriculture’ will grow from approximately 9.58 billion U.S. dollars in 2017 to 23.14 billion U.S. dollars by 2022.
Artificial intelligence and machine learning-based algorithms collect a huge amount of data on a daily basis related to soil quality, humidity, temperature, usage of water, etc. This data is subsequently used to gain real-time insights for understanding the right time to sow a new batch of seeds, active checkups on defective crops and so on which ultimately provides the most efficient way for the entire process from planting till harvest, and eventually the sale of the crops.
AI can significantly make improvements for practices regarding crop management and can help in providing solutions to a lot of challenges faced by the farmers such as weather changes, disease or infestation, or monitoring weeds.
Deep learning applications like Plantix can analyze any possible potential defects or soil deficiencies. It is run by algorithms that are based on big data set collection patterns on plant damages with relation to soil defects, diseases, and pest problems in plants.
While machine learning helps in identifying the different components within the soil. The emphasis although remains on preventing crop failure and maintaining healthy crop production. The farmers can receive an in-depth understanding of the type of soils they have, along with a pathogen screening and microbial evaluation.
Satellites along with machine learning can provide weather predictions simultaneously with crop sustainability analysis. The predictive analysis can help in providing weather-specific diseases. The AI sprayers can accordingly adjust the level and volume of chemicals used in the crop fields, thus utilizing precisely how much is needed.
With the help of Artificial Intelligence and the Internet of Things, the efficiency and management of the supply chain have completely changed. Inventory management is more accurate, there is increased efficiency in warehouse management and reduced operations cost with on-time delivery.
IoT devices like sensors and GPS monitors have introduced transparency in the supply chain by allowing operators to track everything in real-time from shipment’s location and route to the exact temperature and weight of it which is specifically useful for valuable items or chemical compounds.
By utilizing IoT sensors that automatically track the stock levels, it would allow minute-by-minute reports of every commodity in the warehouse or, shipped through an elaborate inventory tracking system. While AI-based algorithms can analyze the collected data and take appropriate measures.
IoT systems can also prove useful in providing a demand forecast. Since the systems automatically collect accurate data throughout the supply chain and within warehouses, the demand forecasts can be highly valid.
AI in addition to IoT devices in supply chain and logistics can improve the quality of management by predicting unforeseen complications by simply understanding the data provided by the IoT. AI can analyze the data and provide solutions based on it.
For example, if one warehouse is running low on stock levels, it would take a supply chain manager to spot the numbers and then act on it, however with the algorithms for AI already in place, it would automatically order replacements.
AI and Machine learning-based principles run highly accurate predictive data for demand forecasting such as predicting the decline for sales of a product and adjusting re-stocking accordingly.
Automation through AI can understand large amounts of data to study patterns and make intelligent decisions.
Pandemic introduced a new and rather improved method of invigilation for examinations through AI-based proctored assessments. Insights gathered now include not only the final score but also how many difficult or easy levels of questions the candidate has attempted, how many of those were they able to get right, how much time they spent on each particular question.
Video proctoring based on a facial recognition system also allows the camera on each individual’s screen to record and evaluate this data along with looking for any background noises, or if the candidate is switching between the screens.
Additionally, it also provides inputs if an individual has taken less time to answer a question that is not practically possible for a particular question then it is able to flag that behavior as well.
Suggested Reading: AI screening has become the latest trend for large scale virtual hiring)
Artificial Intelligence Technologies used for differentiated purposes
A management system powered by an AI can be a useful tool for the HR department to objectively evaluate an employee or candidate’s skill and assess each skill with the business’s strategic goal.
The AI with Text Analysis can evaluate the skill set of a prospective employee and suggest a relevant position.
AI-based talent management software can run a predictive analysis to provide an estimation of key employees before the gap can cost the business. IBM artificial intelligence can determine with 95% accuracy which employees are about to leave their jobs.
Businesses now use AI widely for digital marketing to effectively improve advertising, personalizing or filtering content on their websites, run the predictive analysis for user behavior, etc. AI can help anticipate product demand, enhance consumer satisfaction, provide 24/7 solution chatbots.
Garbage bins and garbage trucks with IoT sensors installed to keep track of the frequency for waste gathering can help adjustments of routes and save fuel, time, and labor. AI can re-direct truck drivers according to the requirements based on data gathered by IoT sensors.
Additionally, garbage bins can be installed with automated sorting for the organic and recyclable matter.
(Also Read: Smart Waste Management using IoT)
Since AI can sift through data and traffic better than any cybersecurity expert, with the help of Text Analysis algorithms it can also look for specific keywords associated with harmful intentions.
Deep Learning as a subset of AI is capable of imitating the way humans acquire new knowledge. Fraud detection uses Deep learning to recognize usual patterns and anomalies. The banking and financial sectors shift towards safe digital transactions are dependent on this technology.
(Suggested Read: How can Artificial Intelligent Combat Cybercrime?)
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