Wireless technology has been a significant element in every electronic system which transmits and receives data using radio waves. In the era or Internet of Things, Big Data and Machine Learning, wireless technologies play an important role to make the system working. Here are some of important applications of wireless technologies in big data analytics.
What is Big Data?
Our daily activities using electronic devices produce massive amount of data in the form of documents, images, videos, social media uploads or interactions. Since the volume of data increasing exponentially every year, we need a much efficient way to store, process and analyze the data in real-time manner.
Big data concept is a system of sophisticated software tools and hardware to collect huge volume of data, securely store in thousands of cloud servers, process with powerful algorithms, analyze and visualize in real-time.
What is the scope of Wireless technology in Big Data?
Since Radio Frequency (RF) technology is used in most of the modern electronic devices as a medium to communicate with other devices and internet, it provides information input (to big data analytics) using wireless sensor networks which gather data from millions of individual nodes and send it to a cloud server. Similarly, Big data analytics also plays a big role in efficient implementation and optimization of RF & wireless technologies like LTE, IoT and 5G as well.
Big Data using Internet of Things
Internet of Things connects billions of smart devices and network of sensors to internet every year to support wide variety of applications. Smart sensors using wireless technology are one of the significant components of IoT.
Smart Home and Building
Smart sensor technology can be used in smart building concept to collect data like room temperature, light, air quality, moisture and movement (using proximity detectors). These sensors will be connected to a wireless network and connected to a cloud server which continuously record data collected from the building. Using analytics of data, efficient energy management (transmission power, peak usage time, idle time, area required improvements) can be implemented.
Users can monitor the data from a remote location and necessary modification can be made. Easier visualization of data via web browser and mobile apps gives users better convenience.
Industrial IoT uses thousands of smart wireless sensors to collect real-time data in the form of temperature, pressure, humidity, liquid flow etc… and transmit this information via wireless network. This huge volume of data will be processed in a cloud server and analytics data will be visible to end users without any delay.
Industries can make use of the data collected from the sensor networks for improvement of the process steps, products and schedule maintenance etc… Engineers can improve product quality and manufacturing stages by continuously monitoring the data. In long run, data analytics will help manufactures in cost reductions, avoid unnecessary machine breakdown etc…
Big data analytics help engineers to develop better lighting solutions in smart city applications. Analysing busy hours, user behaviours, vehicle density etc… will give engineers a useful insight in the area of improvement required.
Data collected from network of sensors can be used to improve smart city applications like traffic management, water management, weather forecast, predictive maintenance of lifts and energy management. Analyzing of vehicles movements, timing and behaviors will be used to develop an efficient traffic control and management.
During accident or emergency, authorities will be notified using automated warning systems.
Autonomous driving concept is developed based on the big data from traffic analytics and user behavior. Self driving cars will use this data and further improvements to algorithms are possible for the safety on road. Smart cars use high end algorithms and artificial intelligence programs to execute an action in split second time frame based on the real-time scenarios in the surroundings.
Traffic data analysis of a geographical area will help to improve signaling systems and thus better efficiency can be achieved.
Big data in Medicine and healthcare
Modern healthcare is another area which companies use big data analytics to help develop and improve patient care solutions, real-time monitoring systems and predictive health analysis. Smart gadgets equipped with wireless technology can continuously monitor body temperature, blood pressure levels, heartbeat variations etc…
In future, smart sensors integrated with wireless technology can predict severe medical conditions like stroke and cardiac arrest before it happens. Analyzing big amount of data from different geographical locations provide researchers an insight about what are the most effective ways to treat a particular medical condition.
Wearable gadgets are getting smarter, capable of handling complex tasks and gather information from individual users. This huge data pool can be analyzed for medical researches and healthcare companies can develop effective solutions in the future.
Big data in 5G applications
One of the major applications of big data in 5G is efficient utilization of spectrum. Analysis of data from thousands of devices will give network operators an insight about pass loss, reflections, diffraction, multipath loss etc… Since 5G uses millimeter waves for communications, millions of small cells have to be deployed during implementation.
Spectral efficiency of each network has to be monitored for better user experience and management. Network operators can improve their transmission efficiency by data analytics and optimum transmission methods (MIMO, beamforming, multiplexing) can be adapted.
Telecom operators will be able to build a flexible network infrastructure using application intelligence with the help of big data analytics in future.
Weather information collected by sensor networks across huge geographical area will be used by smart energy grids like solar energy firms to predict energy source according to changing weather conditions.
Smart cities will make use of smart sensors networks using 5G technology to collect data of air quality, temperature, humidity etc… in long term and these data can be used for future improvements and better planning.
Big data analytics will be used in development of artificial intelligence solutions in various applications in future from, self driving cars, efficient energy management, healthcare and emergency services etc…
Wireless sensors continuously monitoring and collecting data about the engine health, parameters of each flight controls, fuel management, vibration etc… Aircraft manufacturers can access these data to improve their spare parts, predictive maintenance and most importantly offer better passenger safety.
What is the significance of Wireless technologies in big data analytics?
Smart wireless sensors are most significant component in big data analytics to collect useful data from millions of individual nodes across large geographical area. The concept of big data analytics required lot of real-time data of a particular process, environment, and machine status or traffic behavior. All these data are being collected to using wireless sensor network deployed on machines, vehicles, engines, on site or in a factory.
Wireless technologies provides secure connection between these sensor networks, smart devices and internet. Smart sensors and devices can be configured using Wi-Fi, Bluetooth, LoRa, ZigBee, Zwave etc… Wireless sensors provide greater convenience for deployment outside of buildings, on vehicles and simply anywhere depends on the applications.
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