IoT, AoT, AI, ML, Cloud and Big Data together building Super-APPs!

IoT mainstream

According to a recent statistics report, smart cities as planned by various countries there are nearly 3 billion IoT connected devices activated in 2019, an increase of 39 per cent from 2015-2016. Smart commercial buildings are predicted to be the highest user of IoT until 2019, followed by smart homes. Together these two categories will consume just over 6 billion connected devices by 2022. The Internet of Things (IoT) has vast implications for government institutions from city hall to international governing bodies. Tens of billions of physical devices are expected to join the global network by the end of the decade, providing a number of concerns and opportunities for planners, policymakers and regulators.

Analysis of Things (AoT)

It is expected that at places such as industrial zones, office parks, shopping malls, airports or seaports, IoT can also help reduce the cost of energy, spatial management and building maintenance by up to 30 percent. The biggest trend therefore will not just be the increase in connected devices but the data that these devices begin to generate that will create a strong demand for the ‘Analysis of Things’ or AoT. It is the emergence and mainstreaming of AoT that we will see as a significant outcome as the IoT ecosystem comes into play. This analysis or analytics of things will go on to provide disruptive advantages to companies and entities.

Artificial Intelligence and Machine Learning

Artificial intelligence (AI) and machine learning have begun to creep into our lives in more diverse and unexpected ways. Just at a glance, AI algorithms are starting to self-improve search rankings and search results, automated investing, and personal digital assistants. Technology is getting better at making machines better, and in the next few years, we may start inching closer to approaching human-level intelligence with these systems.

IoT, Cloud and Big Data come together

The technology is still in its nascent stage, but the data from devices in the Internet of Things (IoT) became and will continue to become one of the “super-apps” for the cloud and a driver of petabyte scale data explosion. For this reason, we see leading cloud and data companies bringing IoT services to life where the data can move seamlessly to their cloud based analytics engines.

Predictive analytics and its application in different sectors:

# E-commerce

Using customers’ purchase lists, which sections or categories they spend most of their time searching, the products they’re looking out for, etc. helps in designing a personalized ad campaign and highlighting products that they are most likely to buy.

# Banking & Finance Services

Predictive analytics plays a crucial role in banking and finance service as it can immediately identify any fraudulent activity. It can also help in sanctioning of loans. Using the credit scoring of an individual, it can help ascertain if he or she is likely to default.

# Manufacturing

Using predictive analytics, manufacturers can take several preventive measures to maintain a unit’s efficiency levels. Machines which are likely to breakdown or would require a lot of maintenance in the future can be identified using this form of advanced analytics.

# Real Estate

Using predictive analysis, a marketing and sales team can nurture a prospective lead at every step of the process through calls, emails, and SMSes. From enquiries about a particular property to site visits, predictive analysis helps sales representatives select and target their leads in a more efficient manner which eventually plays a significant role in closing leads.

# Government Projects

Modern Governments are using various tools like cyber security, smarter policing using the situational awareness platform, integration of technologies like number plate identification, face recognition and lawful interception amongst others. In fact one the key technologies being implemented today is the face recognition software. This technology has been currently deployed in public areas like bus stands and railway stations. This will help in identifying a blacklisted person as soon as he comes near the camera view, post which the police command and control room can be easily notified about this activity, hastening the response process. In coming months we may see deployment of many mobile apps by police enabling common citizens to connect with control room at times of distress.