Internet of things enabled smart agriculture: Current status, latest advancements, challenges and countermeasures.

It is no wonder that agriculture plays a vital role in the development of some countries when their economies rely on agricultural activities and the production of food for human survival. Owing to the ever-increasing world population, estimated at 7.9 billion in 2022, feeding this number of people has become a concern due to the current rate of agricultural food production subjected to various reasons.

A novel cyber threat intelligence platform for evaluating the risk associated with smart agriculture.

The rapid proliferation of Internet of Things (IoT) devices has brought about a profound transformation in our daily lives and work environments. However, this proliferation has also given rise to significant security challenges, as cybercriminals increasingly target IoT devices to exploit vulnerabilities and gain access to sensitive data. This escalating threat landscape poses a severe issue across diverse domains where IoT is deployed, including agriculture, healthcare, and surveillance.

A review of social background profiling of speakers from speech accents.

Social background profiling of speakers is heavily used in areas, such as, speech forensics, and tuning speech recognition for accuracy improvement. This article provides a survey of recent research in speaker background profiling in terms of accent classification and analyses the datasets, speech features, and classification models used for the classification tasks. The aim is to provide a comprehensive overview of recent research related to speaker background profiling and to present a comparative analysis of the achieved performance measures.

A transformer fine-tuning strategy for text dialect identification.

Online medical consultation can significantly improve the efficiency of primary health care. Recently, many online medical question-answer services have been developed that connect the patients with relevant medical consultants based on their questions. Considering the linguistic variety in their question, social background identification of patients can improve the referral system by selecting a medical consultant with a similar social origin for efficient communication.

Spatial position constraint for unsupervised learning of speech representations.

The success of supervised learning techniques for automatic speech processing does not always extend to problems with limited annotated speech. Unsupervised representation learning aims at utilizing unlabelled data to learn a transformation that makes speech easily distinguishable for classification tasks, whereby deep auto-encoder variants have been most successful in finding such representations. This paper proposes a novel mechanism to incorporate geometric position of speech samples within the global structure of an unlabelled feature set.

Packet-level and IEEE 802.11 MAC frame-level network traffic traces data of the D-Link IoT devices.

With the growth of wireless network technology-based devices, identifying the communication behaviour of wireless connectivity enabled devices, e.g. Internet of Things (IoT) devices, is one of the vital aspects, in managing and securing IoT networks.