There’s been a lot of buzz about how machine learning could help IoT consumer products get smarter. The principle behind IoT is that machines get to communicate with one another through the internet. As the situation currently stands, we have to give most of the machine instructions manually.
The Extent of IoT Consumer Products at the Moment
There are plenty of smart mobile applications that allow you to monitor your home from any location. Others even let you confirm whether or not you locked the door before you left the house. These smart home applications can also allow you to set the thermostat temperature and control it remotely.
Other independent, smart devices at home include the smart coffee maker that prepares your favourite brew at the time most convenient for you. However, you have to input the time manually so that the coffee maker can know when to work. With smart lighting, you have to also have to set when they should come on and go off. You have to tell your smart stereo system to switch itself on if you want to listen to some music.
IOT smart devices have not reached the required level of intelligence to allow them to function by themselves without any user input. You either have to set it or use voice command to make the devices work.
The Possibilities of Machine Learning in IoT Devices
There’s a lot of research going into machine learning and artificial intelligence. Imagine if all your smart consumer products used the information from your smart planner to get things ready for you.
You wake up in the morning, your smart shower starts heating up so that the temperature is just right for you. Depending on your heart rate and mood, the lighting in the bathroom automatically changes to make you feel more motivated. After you finish showering, the coffee maker automatically begins brewing your favourite coffee as you brush your teeth.
The thermostat temperature adjusts itself to the right temperature so that you once you get out of the bathroom, the room feels warm and cozy. After you’ve finished brushing your teeth, you find the smart wardrobe has suggested the right clothes for you depending on that day’s weather forecast. If the clothes have crevices, you put them on the smart ironing machine.
Once you get to the kitchen, your coffee is still hot and waiting for you. You carefully drink your beverage and read your favourite online magazine from your smartphone. Once you finish up with the kitchen area, you put the dishes in the smart dishwasher. The machine automatically cleans the dishes and dries them so that you can still use them when you get back home.
Your smart vehicle starts the engine and warms up as you prepare to get out of the house. You wear your shoes and take your work stuff with you as the door behind you automatically closes, and the thermostat goes on standby. In fact, most of the smart devices will either go off or remain on standby to conserve energy.
This is how the world will look like in the next few years. Machine learning consumer IoT products will make life so much easier.
There is a But…
Before that happens, we need to come up with more stringent measures to curb cyber attacks. Developers can use the spark tutorial to come up with better algorithms for IoT smart devices. The system should also learn to constantly update itself with the latest versions of the program to prevent cyber attacks.
The future of machine learning IoT devices looks bright. There will come a time when most of the devices won’t need any input from us so that they can do their job. However, before that happens, we need to come up with better cybersecurity measures to prevent unwanted breaches.
