The Amalgamation of Internet of Things and Recommender Systems

Abstract

The Internet of Things (IoT) has upgraded the things and regular devices around to smart devices that can interact, share information and collaborate. With the plethora of IoT products, solutions, and workflows available online, the consumer finds it challenging to find the most suitable one. IoT, when integrated with the recommender system, can extend its features to the new space of innovation, usability, viability, and success. Various recommendation techniques can be employed to support users to get the best fit services, applications, sensors, products, and IoT workflows. This article will steer via the basic introduction of the IoT, its building blocks, hardware, software, applications, and its challenges. It analysed scientific articles indexed in the Scopus database with help of biblioshiny tool based on Rstudio software. The analysis is directed on 260 articles to figure out the trending amalgamation of Recommender System with the Internet of Things. Results point to fact that personalized recommendations for IoT-based applications are the most worked on topic by the authors.

An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

“…IoT and its application areas [1][2][3][11][12][13][14][15][16][17][18] The integrity, accuracy, and performance of IoT systems are dependent on the fidelity of sensor data. Sensors are often installed and exposed to harsh conditions, tampering, nasty attacks, attrition, etc., resulting in sensors malfunctioning, erroneous readings, and even failures.…”

“…In recent times, IoT has registered a frantic shift in lifestyles, which has raised the quality of life. IoT developments have accelerated in almost all areas, including manufacturing, production, agriculture, home, and office automation [1][2][3], etc., as shown in Fig. 1.…”

Deep Learning Model for Predicting Consumers’ Interests of IoT Recommendation System

“…Several research works have recognized the significance of recommendation systems for IoT environments and discussed different recommendation techniques including: i) contentbased, ii) collaborative filtering, iii) knowledge-based, and other techniques [16,17,18,19,20]. Other researchers conducted more specific survey papers on IoT recommendation systems related to the fields of context-aware [21], trust [22], and mobile health (m-health) [23].…”

“…The IoT Services Consumers' Tweets Collector is used to get the IoT services consumers tweets based on IoT categories. According to several research works the IoT devices and services are applied in several domains including health, energy, education, transportation, and industry [16,17,18,19,20]. Thus, these application domains were used as categories for IoT service consumers' interests.…”