The rapid adoption of Internet of Things (IoT) devices, cloud platforms, artificial intelligence (AI), intelligent transportation systems, smart healthcare, smart grids, surveillance infrastructure, and connected public services has transformed conventional urban environments into highly interconnected smart cities.

Wireless Sensor Networks (WSNs) are increasingly deployed across critical applications such as military surveillance, environmental monitoring, and smart cities. However, WSNs are susceptible to various security threats due to their resource constraints, open wireless communication, and unattended operation.

There is a growing need for on-device intelligence that can operate under microjoule-level energy constraints and provide trustworthy data due to the proliferation of battery-powered and energy-harvesting Internet of Things (IoT) nodes. History shows that previous methods treated inference, security,

Standard algorithms like AES-128 offer robust and widely-accepted security, but they place a heavy computational and energy burden on endpoints with limited resources, such as Internet of Things (IoT) devices with limited power sources. On the other hand, lightweight alternatives like the ASCON, SPECK, and PRESENT ciphers, which are standardized by NIST, .....

Wireless Sensor Networks (WSNs) form an integral part of the modern Internet of Things (IoT) infrastructure and are used in healthcare, agriculture, smart cities and military applications. However, their open wireless medium, limited processing power and dispersed architecture makes them very vulnerable to a wide range of cyber assaults including Sinkhole, Blackhole, Flooding, Sybil, Wormhole and Selective Forwarding attacks

Big Data Analytics (BDA) and Artificial Intelligence (AI) have become transformative technologies that enable organizations to extract meaningful insights from vast volumes of structured and unstructured data. Their integration has significantly improved decision-making, operational efficiency, customer experience, and innovation across industries such as healthcare, finance, manufacturing, retail, and education.

The identification and classification of medicinal plants play an important role in botanical research, traditional medicine, and biodiversity conservation. However, manual identification based on leaf characteristics can be time-consuming and may require specialized botanical knowledge. This study proposes a Deep Convolutional Neural Network (DCNN)-based approach for the automated classification of medicinal plants using leaf images

Accurate short-term solar irradiance forecasting is essential for efficient solar energy generation, power system management, and the integration of renewable energy resources. However, the nonlinear relationships between solar irradiance and meteorological variables, including temperature, humidity, wind speed, and cloud cover, make reliable forecasting challenging.

Digital transformation has become a strategic priority for organizations seeking to improve efficiency, innovation, and competitiveness in the digital era. Big Data Analytics (BDA) and Artificial Intelligence (AI) play a crucial role in this transformation by enabling organizations to collect, process, and analyze large volumes of data for informed decision-making.