Artificial intelligence matches human performance by learning, deriving conclusions on its own, and executing a clearly defined task. AI uses ML to analyze the data. Machine Learning is an artificial intelligence technology that uses data to automatically discover patterns and trends, resulting in deriving more accurate predictions of future events.
Many organizations are leveraging ML and AI to advance their product development, sales, and overall customer experience. Industries like manufacturing, construction, energy etc. are using this same technology to engage their workforce and more importantly, keep them safe. Organizations today putting a lot of efforts to improve the safety performances in the workplace. Most companies understand the value of a safety culture and have ideologies about what a hyper-vigilant safety culture looks like — where employees are on high alert of their surroundings, perpetually evaluating risks for the task at hand and taking precautions accordingly. Algorithms can identify objects, edges, and velocity because of the advancements of Machine Vision.
Workplace Safety Solutions through AI&ML Computer Vision:
Process and Production Safety - Majority of the workplace facilities have a CCTV system installed on the premises. Computer vision algorithm shall use the live feed from CCTV to detect abnormalities. Machine vision can control different or multiple devices, automating production processes. This increases efficiency and makes the workplace safer as it removes the need for people to be in dangerous areas.
Vision-Based Detection and Tracking - In vision-based object detection and analysis, the mechanism uses vision as the main sensor for the machine to work in real-time. Vision-based object detection and tracking use feature such as shape, color, motion etc. of the object for the detection purpose. The development of vision-based detection and tracking has seen the new high in recent times with the development of robust machine learning algorithms. The deep learning-based object detection models are being practiced compared to the conventional vision technique of object detection and tracking.
PPE Compliant for workplace protection - Personal Protective Equipment (PPE) is the equipment that protects the user against health or safety risks. Not wearing PPE dramatically increases the chances of injuries and in many situations also of financial losses due to fines for injuries and death of workers by not wearing gloves, hairnets, shoe covers, etc. The automation of PPE detection helps companies reduce the risk of accident to the employee, reduce employer liability, improve operational efficiency and provide analytics on the safety of the workplace.
Not only the above mentioned, but AI automation can collect and analyze data for those responsible for the safety of their employees. This allows them to focus on new strategic and innovative ways to improve workplace safety, instead of their time being taken up manually monitoring worksites.AI and Machine Learning are about to change our lives in many good ways. With the help of cloud software, firms will be able to reduce injury and incident rates by over 50%.
The global AI market was valued at $16.06 billion in 2017 and is expected to reach $190.61 billion by 2025, at a CAGR of 36.62% during 2017-2025. Close to 40% or even more of I&O teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity.
Gartner Inc. predicts that 75% of large organizations will hire AI behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk by 2023.
Looking back at the 1990s, technology was limited to computers, the internet, emails, wired telephony, but advancements in technology have led to a sweeping change in its role as an indispensable necessity in our lives and society.
In the subsequent sections, we will see the expanse of AI and ML in various use cases as well as understand their role in one of the most advanced forms of biometric security — facial recognition.What Is Artificial Intelligence (AI)?AI is a technology that simulates human intelligence processes using machines to make cognitive decisions.
Secondly, it adds intelligence to products in the areas of automation, conversational platforms, smart machines, and bots.
Lastly, Artificial Intelligence helps in monetizing data for businesses to stay ahead of the curve.What Is Machine Learning (Ml)?Machine Learning is a subset of AI that mainly focuses on using data and algorithms to mimic human learning.
It converts unstructured data to manageable groups for processing through a process known as dimensionality reduction.On the other hand, neural networks also known as artificial neural networks comprise node layers — an input layer, multiple hidden layers, and an output layer.
In the basic neural network, two or three layers are present whereas a deep neural network consists of more than three layers.How Does ML Work?An ML algorithm has three components:Decision processError FunctionModel OptimizationIn the decision process, an initial input is analysed to make a prediction or estimation of the pattern in the data.
Unstructured data can be filtered with the help of AI algorithms.
How do you get more information from non-sequential information?
These all happened with the help of data mining used by Artificial Intelligence.
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In today’s world, Machine Learning has become the most influential and powerful technology.
Machine learning is the process of giving training to computer systems about how to make accurate predictions when fed data.
Software engineering combined human-created rules with data to create answers to a problem which are Traditionally but machine learning uses data and answers to discover the rules behind a problem.
When we google something or listen to a song, watch video on youtube, take a photo.
Eliminating Manual Tasks : Duplication of data is the biggest dispute faced by the business today.
If any organization is using machine learning for their business than its simply end entry tasks and its incomparable accuracy saves both money & time.
Resolving the problem of bias and variation is only about coping with over-fitting and under-fitting.
Bias is minimized, and the variance concerning the complexity of the model is increased.Read Full Article: https://bit.ly/2NsIaF4
