# Towards Marketing 4.0: Vision and Survey on the Role of IoT and Data Science
## 5 Blueprint Architecture  
In this section, we envision a hyper-connected blueprint architecture to cater to the needs of citizens by connecting people, products, data, and things. The main objective is to enable highly personalised, secure, and privacy-preserving product recommendations to shoppers. However, the application designers need to consider the core requirements below before configuring and deploying the digital advertisement applications. * **Information Freshness**: It is a core requirement to consider the frequent changes in the IoT data and the collection and processing of fresh data that determine the current situation to make informed decisions. Currently, most of the big data processing systems for IoT applications focus on the speed and size of the data to extract the valuable information; however, determining this value in real-time is a daunting task. Furthermore, fresh and accurate data are needed to be captured to establish the correct context of advertisement delivery to each user. * **Fine-grained Targeted Advertising**: Customer preferences, price dynamics, and customer interest in specific products help to establish the right contexts and generate product recommendations. However, when considering the real-time requirements to provide on-the-go advertisement deliveries, the mobility patterns, customer interactions, and proper contextual information are required to target the potential customers at the right time and exact place. * **Fairness**: Targeted advertisements in IoT and smart city scenarios could lead to complex situations where the customers could be easily identified and their information could be linked to predefined advertisement policies. However, the predicate rules in the advertisement applications must be defined to deliver fair and unbiased advertisement without compromising on the data attributes of age, colour, gender, ethnicity, buying power, interaction/non-interaction with smart products, search history, and people protected by the law (e.g., homeless people). * **Privacy Preservation**: IoT-enabled digital advertisement platforms pose serious privacy threats where the customers could be directly or indirectly identified and the targeted advertisements could be delivered to their proximal devices and systems. However, considering the multi-customer interaction with IoT devices, there is a dire need to preserve privacy while equally delivering targeted advertisements. Moreover, the privacy policies must comply with local and regional privacy regulations such as HIPPA (USA), GDPR (EU), and PIPEDA (Canada), to name a few. * **End-to-End Security**: Considering the openness and ubiquity of IoT devices and the collection of personal profiling data, the IoT-enabled digital platforms must ensure the end-to-end security of users, data, devices, and systems. * **Personalisation**: Traditional solutions try to collect the maximum amount of data-points about the customers and execute different profiling mechanisms to maximise the targeted ad delivery. However, considering the multi-device and multi-user phenomenon in IoT-enabled digital advertising platforms, the collection of personal data, maintaining its fresh state, and developing privacy-preserving secure customer profiles require prime attention. System designers are required to create a balance between privacy preservation, personalisation, and data security. Considering the above-mentioned requirements, we envision a components-based layered architecture, as depicted in Figure 3 for: (1) data collection; (2) communication; (3) storage, management, and processing; (4) recommendation generation; (5) advertisement delivery; and (6) security and privacy preservation. * **Data collection layer**: The data input layer needs to allow for interfaces with different types of data sources to collect data about people, products, and places.