The Internet of Things (IoT) refers to the network of interconnected things such as electronic devices, sensors, software, and IT infrastructure that create and add value by exchanging data with various stakeholders such as manufacturers, service providers, customers, other devices, etc., hereby using the World Wide Web technology stack (e.g., WiFi, IPv6). In terms of devices, you can think about heartbeat monitors; motion, noise, or temperature sensors; smart meters measuring utility (e.g., electricity, water) consumption; and so on. Some examples of applications are:

• Smart parking: automatically monitoring free parking spaces in a city;

• Smart lighting: automatically adjusting street lights to weather conditions;

• Smart traffic: optimizing driving and walking routes based upon traffic and congestion;

• Smart grid: automatically monitoring energy consumption;

• Smart supply chains: automatically monitoring goods as they move through the supply chain;

• Telematics: automatically monitoring driving behavior and linking it to insurance risk and premiums.

It speaks for itself that the amount of data generated is enormous and offers an unseen potential for analytical applications.

Pick one particular type of application of IoT and discuss the following:

•  How to use predictive, descriptive, and social network analytics;

•  How to evaluate the performance of the analytical models;

•  Key issues in post-processing and implementing the analytical models; and 

•  Important challenges and opportunities.