Artificial intelligence, specifically deep learning, is gradually changing the agricultural industry as it is introduced to new forms of data analysis and image recognition. It is different from conventional machine learning because this technology generates useful findings from a vast amount of farming data without human intervention. The deep learning models are also very effective in processing data from sensors, drones, and satellites to provide farmers with a detailed view of their crops and fields. This assists to enhance the efficiency in precision farming, and here, water, fertilizer, and pesticide among other necessities are applied only where and when they are needed. It also supports the accomplishment of the maximal producing activity without increasing the risks......

Keywords: Deep learning; Precision Agriculture; Remote sensing; Crop Monitoring; Weed Detection and Management; soil analysis; Satellite Image Analysis; Food Quality Inspection; Harvesting systematization; Irrigation Management; Yield Prediction; Crop Classification and analysis; Sustainable Farming Practice.

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The pharmaceutical supply chain is involved in numerous stakeholders, regulatory requirements, and logistical problems. That makes the guarantee of authenticity, safety, and traceability of pharmaceutical products a continued urgency placed against counterfeit drugs, inefficiencies within the supply chain, and any forms of data vulnerability risks. One need not say much about the realness of the risks associated with using counterfeit drugs. Besides these main problems, the risks are disasters waiting to happen. Blockchain is, therefore, a revolutionary technology that has come into play in the tracking process of pharmaceuticals from the time of manufacturing to when they are used by the consumer. The paper investigates major contemporary issues in pharmaceutical supply chain security, starting from falsification.

Keywords — Supply chain security, drug traceability, counterfeit prevention, decentralized ledger technology.

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Background: Signalized intersections remain global hotspots for pedestrian fatalities, with Abstract Signalized intersections still remain a major location of pedestrian fatalities across the globe, and the conflict of turning vehicles has been labelled as the most common causal factor (WHO,2023; Retting et al., 2003). This systematic review has been prepared in compliance with PRISMA 2020 principles and summarizes the available evidence across the world on the safety performance, the operational efficiency and behavioural implication of pedestrian scramble crossing also known as exclusive pedestrian phases (EPPs).....

Keywords — Pedestrian scramble; exclusive pedestrian phase; diagonal crossing; pedestrian safety; signalized intersection; engineering of traffic; behavioural compliance.

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This paper aims to explore a vehicle intention and driving safety monitoring method based on improved YOLO architecture and Long Short-Term Memory (LSTM) network. By integrating the C2F_EMA module with an LSTM sequential network, the proposed method addresses the limitations of single-frame vision in "long-tail" scenarios (e.g., night-time glare). It significantly enhances the detection accuracy and temporal robustness of vehicle intentions, such as sudden braking and lane changes, thereby providing comprehensive support for driving safety........

Keywords — Intelligent assisted driving; Object detection; C2F_EMA; Edge computing; Temporal arbitration.

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