The Future of Urban Connectivity DOI
Mrutyunjay Padhiary,

Prodipto Roy,

Dipak Roy

et al.

Advances in electronic government, digital divide, and regional development book series, Journal Year: 2024, Volume and Issue: unknown, P. 33 - 66

Published: Nov. 15, 2024

The development of artificial intelligence (AI) and Internet things (IoT) technologies has resulted in a groundbreaking shift urban connectivity that enabled the creation smart cities. This chapter looks at how AI-infused connections have greatly impacted growth IoT communication networks. By utilizing AI, cities can improve public services, utilization assets, increase living standards. Important subjects covered this include predictive maintenance, real-time monitoring, AI-driven data analytics, all which efficiency dependability infrastructure. integration devices AI algorithms settings is examined chapter, featuring concerns including security, privacy, regulatory frameworks being addressed. Through case studies practical examples, it offers thorough explanation redefining encouraging next-generation

Language: Английский

Precision Farming with Drone Sprayers: A Review of Auto Navigation and Vision-Based Optimization DOI
Subrat Jyoti Borah, Mrutyunjay Padhiary,

Laxmi Narayan Sethi

et al.

Journal of Biosystems Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: May 7, 2025

Language: Английский

Citations

0

Improved seeds and motorized tillage: an integrated approach to maximizing agricultural productivity in Burkina Faso DOI
Amandine Laré, Mohamed Amine Boutabba, Kwamivi Mawuli Gomado

et al.

Applied Economics, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 16

Published: May 11, 2025

Language: Английский

Citations

0

Application of LiDAR Sensors for Crop and Working Environment Recognition in Agriculture: A Review DOI Creative Commons
Md Rejaul Karim, Md Nasim Reza, Hongbin Jin

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(24), P. 4623 - 4623

Published: Dec. 10, 2024

LiDAR sensors have great potential for enabling crop recognition (e.g., plant height, canopy area, spacing, and intra-row spacing measurements) the of agricultural working environments field boundaries, ridges, obstacles) using machinery. The objective this study was to review use in crops environments. This also highlights sensor testing procedures, focusing on critical parameters, industry standards, accuracy benchmarks; it evaluates specifications various commercially available with applications feature characterization importance mounting technology machinery effective Different studies shown promising results an airborne LiDAR, such as coefficient determination (R2) root-mean-square error (RMSE) values 0.97 0.05 m wheat, 0.88 5.2 cm sugar beet, 0.50 12 potato height estimation, respectively. A relative 11.83% observed between manual measurements, highest distribution correlation at 0.675 average 5.14% during soybean estimation LiDAR. An object detection 100% found identification three scanning methods: center cluster, lowest point, stem–ground intersection. effectively detect obstacles, which is necessary precision agriculture autonomous navigation. Future directions emphasize need continuous advancements technology, along integration complementary systems algorithms, machine learning, improve performance applications. strategic framework implementing includes recommendations precise testing, solutions current limitations, guidance integrating other technologies enhance digital agriculture.

Language: Английский

Citations

3

The Future of Urban Connectivity DOI
Mrutyunjay Padhiary,

Prodipto Roy,

Dipak Roy

et al.

Advances in electronic government, digital divide, and regional development book series, Journal Year: 2024, Volume and Issue: unknown, P. 33 - 66

Published: Nov. 15, 2024

The development of artificial intelligence (AI) and Internet things (IoT) technologies has resulted in a groundbreaking shift urban connectivity that enabled the creation smart cities. This chapter looks at how AI-infused connections have greatly impacted growth IoT communication networks. By utilizing AI, cities can improve public services, utilization assets, increase living standards. Important subjects covered this include predictive maintenance, real-time monitoring, AI-driven data analytics, all which efficiency dependability infrastructure. integration devices AI algorithms settings is examined chapter, featuring concerns including security, privacy, regulatory frameworks being addressed. Through case studies practical examples, it offers thorough explanation redefining encouraging next-generation

Language: Английский

Citations

2