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Machine Learning

The Intersection Of Intelligence – Ml With IoT

Uber connected drivers and ride seekers, AirBnB connected property owners with people looking for properties and the story has been similar for many companies and technologies so far. With the intersection of IoT and ML, we expect our everyday devices to be more efficient, more “smart” and more customized to the needs of individuals. IoT is found in 77% of all electronic products sold in 2019, this number is expected to grow but not in the way we think IoT as, in fact, these devices will not have ML integrated into them as we are expecting. So instead of dancing around the phrase lets look at how and where this intersection is feasible? Where it is being used and the future of it.   


If we are asking about the limitations of this intersection, the biggest limitation is the cost of integration of these two technologies, this integration has been seen in medical equipment, manufacturing equipment, autonomous cars and more. The problem has been implementing this technology in everyday consumer electronics, there is lack of infrastructure to send and receive data, lack of hardware to implement the developments from the data extracted and the scope for expansion of a device which is supposed to fit within the palm of a hand. We can have an air conditioner to adjust its setting with respect to geographical location and its conditions such as humidity and outside temperature, the challenge will be to make these decisions on a real-time basis. Now we will look at some of the working examples of this intersection as of now.


Tesla electric car singlehandedly changed how the world viewed electric cars, from a close proximity commuter car to a practical everyday car. Tesla cars have been combining real-world and real-time information to tweak its performance, Tesla’s automated driving also has been way ahead of its competition. All of this has been due to constant interaction of both of these technologies, somewhere else where IoT and ML have been big waves is in the healthcare sector. IoT and Ml embedded in devices such as scanning machines have helped medical professionals with accurately diagnosing health ailments. The concept of smart homes and cities are built on the foundations of ML and IoT. Devices are connected on such a scale that data drives real-world decisions by officials, cities can achieve operational efficiency which can reduce pollution, reduce wastage of resources and more.    


As technology seeps into all aspects of our everyday life, one of the biggest advantages will be saving the wastage of precious resources, as cities, buildings, homes and institutions will be connected digitally. Imagine an agrarian sector driven by data where the water delivery systems are customized to the crops which have been planted, the agriculture sector is one of the sectors where an overhaul is needed and IoT and ML can be one of the combinations of technologies which can power it.  Soon this technology will be everywhere, invisible to us but will power a green future.   




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