Artificial intelligence (AI) is revolutionizing biotechnology by accelerating research and development, improving precision, and enabling innovations across multiple fields within biotech. For engineers, AI offers powerful tools to analyze complex biological data, optimize drug discovery, enhance genetic research, and automate laboratory processes, fundamentally changing how biotech solutions are designed, tested, and produced. AI-Driven Drug Discovery and Development One of the most impactful applications of AI in biotech is speeding up drug discovery. AI algorithms analyze vast chemical and biological datasets to predict compound interactions, bioactivity, toxicity, and optimize lead candidates. This drastically reduces the time and cost compared to traditional trial-and-error methods. Engineers play a critical role by designing AI models that handle simulations, data integration, and prediction, strengthening personalized medicine and clinical trial optimizations. Geno...
Arya College of Engineering & I.T. says communication protocols define standardized rules for data exchange between devices, categorized by OSI/TCP-IP layers to ensure reliable transmission in networks like Industrial IoT or edge computing systems, critical for engineering projects. They split into communication (data transfer), management (monitoring/control), and security types, with transport-layer protocols like TCP (reliable, connection-oriented) and UDP (fast, connectionless) forming the backbone alongside application-layer ones like HTTP for web data. Transport Layer Protocols TCP guarantees ordered delivery with error-checking and acknowledgments, ideal for file transfers or streaming in cloud simulations, while UDP prioritizes speed for real-time video/audio in AR/VR prototypes without retransmissions. RTP pairs with UDP for low-latency media over IP, supporting SIP in VoIP for remote engineering collaborations. SCTP adds multi-streaming for telephony-like reli...