• Hardik Khamele
• Dr Goldi Soni
• Pawan Kumar

The Internet of Things (IoT) has revolutionized industries by connecting diverse physical devices to the internet, enabling seamless communication and data exchange across a broad spectrum of objects, from household appliances to sophisticated industrial machinery. This connectivity generates massive volumes of diverse, rapidly produced data, posing significant challenges in its efficient management and analysis. To address these challenges, specialized data structures and algorithms have been developed to meet the unique demands of IoT applications. Time-series databases, for example, are tailored to manage data collected over time, helping to identify trends and patterns. Similarly, graph databases are invaluable for mapping and analyzing relationships between data points, providing insights into how devices interact within a network. Key-value stores are designed for quick data retrieval, ensuring efficient access through unique identifiers, while streaming processing techniques enable real-time data analysis, allowing immediate responses to events or changes. Machine learning algorithms enhance IoT systems by identifying complex data patterns, predicting trends, and automating decision-making processes. Meanwhile, distributed computing solutions ensure scalability and efficiency by distributing workloads across multiple systems, allowing for the seamless handling of massive datasets. Together, these technologies transform raw data into actionable insights, driving optimization, efficiency, and productivity across industries. This capability not only enhances operations but also fosters innovation, paving the way for smarter, more connected systems. By addressing the challenges of IoT data management, these advancements open doors to new possibilities, improving business practices and enriching everyday life with intelligent solutions.

IoT (Internet of Things), Data Structures, Algorithms, Time-Series Databases, Graph Databases, Key-Value Stores, Machine Learning, Deep Learning, Distributed Computing, Stream Processing, Scalability, Security, Privacy, Edge Computing, Blockchain.

"Data Structures and Algorithms for Internet of Things (IoT): A Comprehensive", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 12, page no.c121-c127, December-2024, Available :http://www.jetir.org/papers/JETIR2412211.pdf

"Data Structures and Algorithms for Internet of Things (IoT): A Comprehensive", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 12, page no. ppc121-c127, December-2024, Available at : http://www.jetir.org/papers/JETIR2412211.pdf