Remote Assistant Technology for Real Time Monitoring of the Agricultural Farmland across the Districts Using Smart Positioning IoT
International Journal of Electrical and Electronics Engineering |
© 2024 by SSRG - IJEEE Journal |
Volume 11 Issue 9 |
Year of Publication : 2024 |
Authors : Sumalatha Aradhya |
How to Cite?
Sumalatha Aradhya, "Remote Assistant Technology for Real Time Monitoring of the Agricultural Farmland across the Districts Using Smart Positioning IoT," SSRG International Journal of Electrical and Electronics Engineering, vol. 11, no. 9, pp. 112-127, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I9P110
Abstract:
Precision agriculture, land surveys, and positioning measures are useful to society for accurate mapping of boundaries in the local agricultural area. An existing approach uses Global Navigation technologies with a deviation accuracy of 10% with geo fencing mechanism. However, a Navigation system needs the support of advanced positioning technology to improve positioning accuracy. In the paper, a novel approach to positioning is proposed. The approach includes a digital classification and optimization of area mapping, enhancement of correlation data, analysis through an expert system and clustering of delineation zones using an optimized Artificial Bee Colony algorithm. Precision accuracy is achieved by the correction of zonal map boundaries and radio frequency sensors. The real time kinematics technique is applied further to do the deviation corrections, improvement, and optimization. An experiment was carried out in real time between two districts, namely Bangalore and Tumakuru, where the distance was nearly 60 km. An optimized artificial bee colony algorithm is used to correct errors and improve positioning accuracy. The real time field trail data is analyzed, calibrated, and improved further to obtain a precision accuracy of 99.9%.
Keywords:
Precision accuracy, Remote sensing, Real time kinematics, IoT, Satellite navigation, Localization, Delineation, Positioning, Assistant technology.
References:
[1] James A. Slater, and Stephen Malys, “WGS 84 - Past, Present and Future,” Advances in Positioning and Reference Frames, pp. 1-7, 1998.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Siyao Dang, Haisheng Huang, and Xin Li. “About the Parsing of NMEA-0183 Format Data Streams in GPS,” Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, pp. 1282-1289, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Sungchan Jeong et al., “Tracking Diurnal to Seasonal Variations of Gross Primary Productivity Using a Geostationary Satellite, GK-2A Advanced Meteorological Imager,” Remote Sensing of Environment, vol. 284, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Wanxin Xiao et al., “An Automated Algorithm to Retrieve the Location and Depth of Supraglacial Lakes from ICESat-2 ATL03 Data,” Remote Sensing of Environment, vol. 298, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[5] David Vieira et al., “Positioning and Attitude Determination for Precision Agriculture Robots Based on IMU and Two RTK GPSs Sensor Fusion,” IFAC-Papers on Line, vol. 55, no. 32, pp. 60-65, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Anam M. Khan et al., “Reviews and Syntheses: Ongoing and Emerging Opportunities to Improve Environmental Science Using Observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellites,” Biogeosciences, vol. 18, no. 13, pp. 4117-4141, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Agata M. Wijata et al., “Taking Artificial Intelligence into Space through Objective Selection of Hyperspectral Earth Observation Applications: To bring the “Brain” Close to the “Eyes” of Satellite Missions,” IEEE Geoscience and Remote Sensing Magazine, vol. 11, no. 2, pp. 10-39, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[8] M. Bietresato et al., “A Tracked Mobile Robotic Lab for Monitoring the Plants Volume and Health,” 2016 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), Auckland, New Zealand, pp. 1-6, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[9] André Silva Aguiar et al., “Localization and Mapping for Robots in Agriculture and Forestry: A Survey,” Robotics, vol. 9, no. 4, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Tomoaki Miura et al., “Improved Characterization of Vegetation and Land Surface Seasonal Dynamics in Central Japan with Himawari-8 Hyper Temporal Data,” Scientific Reports, vol. 9, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Norman Kerle et al., “UAV-Based Structural Damage Mapping: A Review,” ISPRS International Journal of Geo-Information, vol. 9, no. 1, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Berkay Bahadur, “Real-Time Single-Frequency Precise Positioning with Galileo Satellites,” The Journal of Navigation, vol. 75, no. 1, pp. 124-140, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Nicola Angelo Famiglietti et al., “A Test on the Potential of a Low Cost Unmanned Aerial Vehicle RTK/PPK Solution for Precision Positioning,” Sensors, vol. 21, no. 11, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Farzaneh Zangenehnejad, and Yang Gao, “GNSS Smartphones Positioning: Advances, Challenges, Opportunities, and Future Perspectives,” Satellite Navigation, vol. 2, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Cong Khai Pham et al., “Research and Development of Real-time High-precision GNSS Receivers: A Feasible Application for Surveying and Mapping in Vietnam,” Journal of the Polish Mineral Engineering Society, vol. 1, no. 2, pp. 391-404, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Yang Ye et al., “A Feasible Framework to Downscale NPP-VIIRS Nighttime Light Imagery Using Multi-Source Spatial Variables and Geographically Weighted Regression,” International Journal of Applied Earth Observation and Geoinformation, vol. 104, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Guangtong Xu et al., “Trust-Region Filtered Sequential Convex Programming for Multi-UAV Trajectory Planning and Collision Avoidance,” ISA Transactions, vol. 128, Part B, pp. 664-676, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Fabio Marcelo Breunig et al., “Delineation of Management Zones in Agricultural Fields Using Cover-Crop Biomass Estimates from PlanetScope Data,” International Journal of Applied Earth Observation and Geoinformation, vol. 85, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Kathryn Elmer, and Margaret Kalacska, “A High-Accuracy GNSS Dataset of Ground Truth Points Collected within Iles-de-Boucherville National Park, Quebec, Canada,” Data, vol. 6, no. 3, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Davis Dinkov, and Atanas Kitev, “Advantages, Disadvantages and Applicability of GNSS Post-Processing Kinematic (PPK) Method for Direct Georeferencing of UAV Images,” Proceedings of the 8th International Conference on Cartography and GIS, Nessebar, Bulgaria, vol. 1, pp. 747-759, 2020.
[Google Scholar]
[21] Yulong Ge et al., “An Analysis of BDS-3 Real-Time PPP: Time Transfer, Positioning, and Tropospheric Delay Retrieval,” Measurement, vol. 172, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Jacek Paziewski et al., “An Analysis of Multi-GNSS Observations Tracked by Recent Android Smartphones and Smartphone-only Relative Positioning Results,” Measurement, vol. 175, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Dengshuai Chen et al., “The Delineation of Ecological Redline Area for Catchment Sustainable Management from the Perspective of Ecosystem Services and Social Needs: A Case Study of the Xiangjiang Watershed, China,” Ecological Indicators, vol. 121, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[24] M.H.N. Talib et al., “An Improved Simplified Rules Fuzzy Logic Speed Controller Method Applied for Induction Motor Drive,” ISA Transactions, vol. 105, pp. 230-239, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Weicheng Xu et al., “Cotton Yield Estimation Model Based on Machine Learning Using Time Series UAV Remote Sensing Data,” International Journal of Applied Earth Observation and Geoinformation, vol. 104, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Yong Ge et al., “Geoscience-Aware Deep Learning: A New Paradigm for Remote Sensing,” Science of Remote Sensing, vol. 5, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Mark Bolinger, and Greta Bolinger, “Land Requirements for Utility-Scale PV: An Empirical Update on Power and Energy Density,” IEEE Journal of Photovoltaics, vol. 12, no. 2, pp. 589-594, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Yali Zhang, and Mingshi Li, “A New Method for Monitoring Start of Season (SOS) of Forest Based on Multisource Remote Sensing,” International Journal of Applied Earth Observation and Geoinformation, vol. 104, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Yi He et al., “A Unified Network of Information Considering Superimposed Landslide Factors Sequence and Pixel Spatial Neighbourhood for Landslide Susceptibility Mapping,” International Journal of Applied Earth Observation and Geoinformation, vol. 104, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[30] Andreas A. Beckert et al., “The Three-Dimensional Structure of Fronts in Mid-Latitude Weather Systems in Numerical Weather Prediction Models,” Geoscientific Model Development, vol. 16, no. 15, pp. 4427-4450, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[31] Huidi Wang et al., “The Relaxed Implicit Randomized Algebraic Reconstruction Technique for Curve and Surface Reconstruction,” Computers & Graphics, vol. 102, pp. 9-17, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[32] A.H. Mazinan, and M. Shahi, “On High-Resolution Manoeuvres Control via Trajectory Optimization,” Sadhana, vol. 42, pp. 245-255, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[33] Qun Ma et al., “Spatial Scaling of Urban Impervious Surfaces across Evolving Landscapes: From Cities to Urban Regions,” Landscape and Urban Planning, vol. 175, pp. 50-61, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[34] Xuebin Yang et al., “Mapping Forest in the Southern Great Plains with ALOS-2 PALSAR-2 and Landsat 7/8 Data,” International Journal of Applied Earth Observation and Geoinformation, vol. 104, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[35] Piyapong Suwanno et al., “GIS-Based Identification and Analysis of Suitable Evacuation Areas and Routes in Flood-Prone Zones of Nakhon Si Thammarat Municipality,” IATSS Research, vol. 47, no. 3, pp. 416-431, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[36] Andre Broekman, and Petrus Johannes Grabe, “A Low-Cost, Mobile Real-Time Kinematic Geolocation Service for Engineering and Research Applications,” HardwareX, vol. 10, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[37] Bumairiyemu Maimaiti et al., “Urban Spatial Expansion and Its Impacts on Ecosystem Service Value of Typical Oasis Cities around Tarim Basin, Northwest China,” International Journal of Applied Earth Observation and Geoinformation, vol. 104, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[38] Feng Yang, and Zhenzhong Zeng, “Refined Fine-Scale Mapping of Tree Cover Using Time Series of Planet-NICFI and Sentinel-1 Imagery for Southeast Asia (2016–2021),” Earth System Science Data, vol. 15, no. 9, pp. 4011-4021, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[39] Cheng Zhong et al., “Landslide Mapping with Remote Sensing: Challenges and Opportunities,” International Journal of Remote Sensing, vol. 41, no. 4, pp. 1555-1581, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[40] Yuri Taddia et al., “Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTK,” Remote Sensing, vol. 12, no. 19, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[41] Vinod Singh Jadon, and K.P. Ray, “Analysis of Harmonics and Their Mitigation for a Tuned Cylindrical Monopole Antenna,” Sadhana, vol. 48, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[42] Prithish Chand et al., “Low-Profile Compact Printed Monopole Antenna for Satellite-Bas1ed AIS Application,” Defence Science Journal, vol. 70, no. 2, pp. 175-182, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[43] Moritz K. Lehmann et al., “Analysis of Recurring Patchiness in Satellite-Derived Chlorophyll a to Aid the Selection of Representative Sites for Lake Water Quality Monitoring,” International Journal of Applied Earth Observation and Geoinformation, vol. 104, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[44] Finu Shrestha et al., “A Comprehensive and Version-Controlled Database of Glacial Lake Outburst Floods in High Mountain Asia,” Earth System Science Data, vol. 15, no. 9, pp. 3941-3961, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[45] Nico Lang et al., “A High-Resolution Canopy Height Model of the Earth,” Nature Ecology & Evolution, vol. 7, pp. 1778-1789, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[46] David P. Roy et al., “A Global Analysis of the Temporal Availability of PlanetScope High Spatial Resolution Multi-Spectral Imagery,” Remote Sensing of Environment, vol. 264, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[47] Ruben Ferrer Velasco et al., “Towards Accurate Mapping of Forest in Tropical Landscapes: A Comparison of Datasets on how Forest Transition Matters,” Remote Sensing of Environment, vol. 274, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[48] Jingfeng Xiao et al., “Emerging Satellite Observations for Diurnal Cycling of Ecosystem Processes,” Nature Plants, vol. 7, pp. 877-887, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[49] Joe Breen et al., “POWDER: Platform for Open Wireless Data-Driven Experimental Research,” Proceedings of the 14th International Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization (WiNTECH), pp. 17-24, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[50] Cong Miao, and Yu Wang, “Interpolation of Non-Stationary Geo-Data Using Kriging with Sparse Representation of Covariance Function,” Computers and Geotechnics, vol. 169, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[51] Yu Yao et al., “Egocentric Vision-Based Future Vehicle Localization for Intelligent Driving Assistance Systems,” 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, pp. 9711-9717, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[52] Mahek Vyas et al., “Implementation and Testing of Single Point Positioning on IRNSS/NavIC Receiver Data,” International Journal of Communication Systems, vol. 37, no. 13, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[53] Xingzhi Chang et al., “Design of a 3D Space Early Warning System for High Precision Positioning Technology of Beidou and Analysis of Differential Positioning Accuracy,” Measurement: Sensors, vol. 33, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[54] Nandakumaran Nadarajah et al., “The Mixed-Receiver BeiDou Inter-Satellite-Type Bias and its Impact on RTK Positioning,” GPS Solutions, vol. 19, pp. 357-368, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[55] Brian Paden et al., “A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles,” IEEE Transactions on Intelligent Vehicles, vol. 1, no. 1, pp. 33-55, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[56] Tarik Kazaz et al., “Delay Estimation for Ranging and Localization Using Multiband Channel State Information,” IEEE Transaction on Wireless Communications, vol. 21, no. 4, pp. 2591-2607, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[57] Nitin Kumar Vishwakarma, Ragini Shukla, and Ravi Mishra, “A Review of Different Methods for Implementing Smart Agriculture on An IoT Platform,” SSRG International Journal of Computer Science and Engineering, vol. 7, no. 12, pp. 5-8, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[58] Ahmed Salim, Ahmed M. Khedr, and Walid Osamy, “Enhancing IoT-Enabled Sustainable Smart Cities with Secure and Energy-Aware Data Collection Using Meta-Heuristic Technique,” IEEE Sensors Journal, vol. 24, no. 14, pp. 22974-22991, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[59] Denes Farago, Balint Maczak, and Zoltan Gingl, “Enhancing Accuracy in Actigraphic Measurements: A Lightweight Calibration Method for Triaxial Accelerometers,” IEEE Access, vol. 12, pp. 38102-38111, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[60] Jayson P. Van Marter et al., “A Multichannel Approach and Testbed for Centimeter-Level WiFi Ranging,” IEEE Journal of Indoor and Seamless Positioning and Navigation, vol. 2, pp. 76-91, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[61] Haiyun Yao et al., “A Benchmark of Absolute and Relative Positioning Solutions in GNSS Denied Environments,” IEEE Internet of Things Journal, vol. 11, no. 3, pp. 4243-4273, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[62] Chandni Bajaj et al., “GPS-Integrated RFID Antenna with AMC Backing for IoT-Based Sensing and Tracking Applications,” IEEE Transactions on Antennas and Propagation, vol. 72, no. 2, pp. 1929-1934, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[63] Maria Bermudez Arboleda et al., “Orientation Aware Intelligent 3-D Cubic Antenna System with Automated Radiation Pattern Reconfigurability,” IEEE Open Journal of Antennas and Propagation, vol. 3, pp. 812-823, 2022.
[CrossRef] [Google Scholar] [Publisher Link]