Big Data Analytics in Society

Availability of processing power and storage space at a decreasing cost with intelligent software tools to parse big data set has spread the usage of big data analytics across every industry (Val et al., 2017). Today, big data analytics is playing pivotal role in marketing, manufacturing, seismic data, health care, telecommunications, geolocation, genetics etc. industries to break new grounds. Cloud hosting has helped in bringing the cost down of software and hardware resources with pay-as-you-go elastic model which has hampered growth in the past but not anymore.

Some of the advancements which are likely to happen in close future are:

1. Smart City

2. Smart Agriculture

3. Supply Chain, retail and logistics

Smart City

There are several efforts underway with regards to Smart city (Yaqoob et al., 2016) which encompasses smart transportation, smart traffic light system etc. With the intelligent and optimized adaptation of timing for the traffic light system, there will be less bottlenecks and congestion points on the roads resulting in reduction in travel time (Zungeru et al., 2017). Similarly, smart transportation using tracking techniques will help in managing congestion cases in severe weather conditions, accidents etc. but also smart diagnostics will keep an eye on the upkeep of engine and vehicle maintenance to avoid breakdown. Further improvement in telematics in case of auto breakdown will improve the time to remove the broken car from the road which will enhance the on-road experience overall. Internet of People (Murillo et al., 2015) is another term coined which enables the improvement of connection between people and IoT; for instance currently Waze mobile application incorporates the reporting of accident by people which is being used by Google maps etc. for traffic rerouting purposes.

Smart Agriculture

Since big data is all about collecting data from variety of sources which can be utilized for agriculture sector (Yaqoob et al., 2016) by gathering moisture level of soil, humidity, weather forecast etc. which can trigger automatic actions like timely and controlled irrigation, humidity control for fungus, water conservation in the event of rain forecast etc. Although this is already in practice but based on more data certain geographical location can be optimized for a particular crop with the highest yield and quality using less resources and efforts.

Supply Chain, Retail & Logistics

Tracking the goods while on the road and optimizing the route can improve the efficiency of logistics from farm to store, factory to warehouse, and warehouse to retail store and store to customer delivery (Yaqoob et al., 2016). From retail store perspective, automatic ordering of an item running out from store shelves will improve the availability and customer experience. Demand and supply can be monitored closely for the optimal delivery of goods from the originating source all the way to customer.

Reference:

Zungeru, A., Ijemaru, G. & Ang, L. (2017). Big Sensor Data Systems for Smart Cities. IEEE Internet of Things.

Yaqoob, I., Siddiqa, A., Nasaruddin, F., Marjani, M., Karim, A., Hashem, T., Gani, A. & Abaker, I . (2016). Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges. IEEE Access.

Val, P., Steed, A., Song, H., Lv, Z. & Jo, M. (2016). Next-Generation Big Data Analytics: State of the Art, Challenges, and Future Research Topics. IEEE Transactions on Industrial Informatics.

Murillo, J., Mikkonen, T., Makitalo, N., Miranda, J., Canal, C., Berrocal, J. & Garcia, J. (2015). From the Internet of Things to Internet of People. IEEE Internet Computing, 40-47