Adil Bashir – författare

This book examines how Artificial Intelligence is reshaping modern agriculture, offering pathways toward sustainability, resilience, and efficiency. Through contributions on AI-powered image and video analysis, IoT-driven sensor networks, and drone-based monitoring, it highlights the practical applications of intelligent systems in crop health assessment and yield optimization. The chapters also address pressing challenges such as pest detection, storage loss management, and ethical considerations in AI-based decision-making. From horticulture to large-scale farming, the volume emphasizes the role of machine learning in crop recommendation, pest control, and fertilizer optimization, while exploring the integration of visual analytics for scalable agricultural monitoring. By bridging technological advances with real-world agricultural practices, the book demonstrates how AI fosters sustainable farming and global food security. It is an essential resource for scholars, students, practitioners, and policymakers in agriculture, computer science, and environmental studies who seek to harness innovation for regenerative farming.

Master's Thesis from the year 2013 in the subject Computer Science - Internet, New Technologies, grade: 8.12, , course: M. Tech, language: English, abstract: Wireless sensor network (WSN) is an emerging imperious leading technology of the current century that presents great promise for various pioneering applications. The use of sensor networks should keep developing, mainly in the fields of scientific, logistic, healthcare and military applications. Sensor networks interact and collect sensitive data and operate in unattended hostile environments, thus it is imperative to pay attention to the security of wireless sensor networks as they are highly prone to threats. For successful operation of the nodes, it is important to maintain the security and privacy of the transmitted data as well as the data stored at nodes. The different security protocols and models used in the wired and other wireless networks such as ad-hoc networks cannot be used in WSNs because the sensor size poses significant restrictions, mainly in terms of energy autonomy and node lifetime, as the batteries have to be too tiny. Also, the existing security protocols in these constrained networks are not sufficiently energy efficient, which is the real motivation behind this work. In this thesis, a light-weight dynamic security algorithm titled An Energy Efficient and Dynamic Security Protocol (EEDSP) for wireless sensor networks has been proposed and implemented at nodal level. We also implement an existing algorithm and then carry out the performance analysis of both the algorithms in terms of energy consumptions, node lifetime and memory requirements at source and intermediate nodes to verify the improvement in our protocol s results.

Master's Thesis from the year 2020 in the subject Computer Sciences - Artificial Intelligence, grade: 9.30, , language: English, abstract: The application of DL techniques in steganography has greatly increased the efficiency of steganographic concealment systems, leading to a substantial improvement in safety risks. To counter this, the researchers shifted to steganalysis, the method of detecting steganographic material. In practice, steganalysis is being used in a security framework that operates like a spam-filter to prevent the transmission of malicious steganographic content through networks. Newer steganalysis methods, however, have shown promising results, but they remain both fairly inefficient and non-robust. Steganography is the mechanism by which data are hidden inside an ordinary (non-secret) file to evade detection. Although encryption is intended to hide data information, steganography is intended to conceal data existence. Steganography can also hide new form of communication by hiding the existence of data, and thus provide behavioral protection. Steganography provides behavioral protection and plays a critical role in safeguarding the privacy of information. Although steganographic concealment systems are routinely used for benign activities, bad actors can also use them to transmit malicious information using ordinary files such as photographs, thus posing a risk to security. Because current network defenses do not search images for steganographic content, the transmission of malicious steganographic content cannot be effectively blocked. Hackers may thus use steganography to transfer vulnerabilities or other compromising data in an untraceable fashion through networks.