The recommender systems are deployed on the Web for reducing cognitive overload. It uses different parameters, such as profile information, feedbacks, history, etc., as input and recommends items to a user or group of users. Such parameters are easy to predict and calculate for a single user on a personalized device, such as a personal computer or smartphone. However, watching the Web contents on a smart TV is significantly different from other connected devices. For example, the smart TV is a multi-user, lean-back supported device, and normally enjoyed in groups. Moreover, the performance of a recommender system is questionable due to the dynamic interests of groups in front of a smart TV. This paper discussed in detail the existing recommender system approaches in the context of smart TV environment. Moreover, it highlights the issues and challenges in existing recommendations for smart TV viewer(s) and presents some research opportunities to cope with these issues. The paper further reports some overlooked factors that affect the recommendation process on a smart TV. A subjective study of viewers’ watching behavior on a smart TV is also presented for validating these factors. Results show that apart from all technological advancement, the viewers are enjoying smart TV as a passive, lean-back device, and mostly used for watching live channels and videos on the big screen. Furthermore, in most households, smart TV is enjoyed in groups as a shared device which creates hurdles in personalized recommendations. This is because predicting the group members and satisfying each member is still an issue. The findings of this study suggest that for precise and relevant recommendations on smart TVs, the recommender systems need to adapt to the varying watching behavior of viewer(s).

The user interface (UI) is a primary source of interaction with a device. Since the introduction of graphical user interface (GUI), software engineers and designers have been trying to make user-friendly UIs for various computing devices, including smartphones, tablets, and computers. The modern smart TV also comes with built-in operating systems. However, little attention has been given to this prominent entertainment device, i.e., smart TV. The technological advancement and proliferation of smart TV enabled the manufacturer to provide rich functionalities and features; however, this richness resulted in more clutter and attention-demanding interfaces. Besides, smart TV is a lean-back supporting device having a diverse range of users. Therefore, smart TV’s usability and user experience (UX) are questionable due to diverse user interests and limited features of traditional remote controls. This study aimed to discuss and critically analyze the features and functionalities of the existing well-known smart TV UIs of various operating systems in the context of usability, cognition, and UX. Moreover, this study highlights the issues and challenges in the current smart TV UIs and recommends some research opportunities to cope with the smart TV UIs. This study further reports and validates some overlooked factors affecting smart TV UIs and UX. A subjective study and usability tests from diverse users are presented to validate these factors. The study concludes that a one-size-fits-all UI design is unsuitable for shared devices, i.e., smart TV. This study further recommends a personalized adaptive UI, which may enhance the learnability and UXs of the smart TV viewers.

Smart TV is a television set that has the capabilities of processing, storage, and connectivity. Besides these features, smart TV brings app-based entertainment, which is beyond the scope of legacy TV systems. Being a connected device, smart TV is facing numerous challenges not only in the form of security and privacy but also usability and accessibility. For example, a smart TV has access to diverse data sources. Therefore, searching for desired content on a smart TV is difficult and time-consuming. Although, Electronic Program Guides (EPGs) provide some facilities for searching desired contents; yet, scrolling a long list of programs is not welcomed by the viewers. In this paper, we are reviewing the inter and intra-app navigational complexities and their effects on usability, learnability, and cognition. Although, smart TV manufacturers are trying to produce smart TVs with simple to use interfaces; yet, the existing smart TVs interfaces have accessibility and usability issues that are discussed in this paper. This paper further presents some recommendations and guidelines for the design of a universal user interface for smart TV.

Blind people face multiple challenges in performing their daily activities, such as localization, navigation, and communication with other people following the social status of the ambient environment. The outdoor navigation and localization are mitigated through assistive technologies, such as white cane, smartphones, and Global Positioning System (GPS). However, little attention has been paid to assisting a blind person in judging the room environment, occupants in a room, communicating with an intended person, social status, and so on. This study attempts to provide cognitive assistance to blind people in predicting room types and finding the intended person to communicate their message by understanding their ambient environment and social status in terms of their age, gender, and the number of people inside a room. The proposed solution uses the microphone and speaker to recognize room types and a camera for understanding the ambient environment and social status. The information is conveyed to the blind person through haptic feedback. We analyzed different evaluation metrics, including the movement of people, ambient sounds, orientation, and position. We conducted an extensive user study to validate the proposed solution in real-world scenarios and achieved 87.64% accuracy in room type recognition in 11 rooms, 64.57% gender recognition, 61.73% age group, and 61.71% correctly identified the number of people.