AI SearchEnhancing crop yield predictions with ensemble machine learning model using IoT environmental data and UAV vegetation indices : (Record no. 38437)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03399nas a2200373 a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260818100103.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260407s20249999th u ms tm 000 eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12498695 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Diss. no.ICT-24-02 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Nisit Pukrongta |
| 245 10 - TITLE STATEMENT | |
| Title | Enhancing crop yield predictions with ensemble machine learning model using IoT environmental data and UAV vegetation indices : |
| Remainder of title | a case study of Maize |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Pathum Thani, Thailand : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 92 leaves : |
| Other physical details | ill. |
| Accompanying material | +1 online resource |
| 490 1# - SERIES STATEMENT | |
| Series statement | Dissertation ; |
| Volume/sequential designation | no. ICT-24-02 |
| 500 ## - GENERAL NOTE | |
| General note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Information and Communication Technologies |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (Ph.D.) - Asian Institute of Technology, 2024 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This dissertation introduces a weighted ensemble prediction model, PEnsemble4model, that combines several machine learning models to enhance the accuracy of maize yield at early growth stages. Utilizing both unmanned aerial vehicle (UAV) imagery and In ternet of Things (IoT) enabled sensors collected environmental data, as well as soil and plant nutrient attributes, the model offers a detailed, data-driven methodology for maize yield prediction. Given the increasing global demand for maize and the crop{u2019}s suscep tibility to weather fluctuations, the enhancement of predictive capabilities is crucial. The PEnsemble 4 model meets this demand by utilizing extensive datasets that include soil characteristics, nutrient levels, weather conditions, and UAV-captured vegetation imagery. It employs a combination of Huber and M estimates to analyze temporal varia tions in vegetation indices, particularly Chlorophyll-red edge index (CIre) and Normal ized difference red edge index (NDRE), which are key indicators of canopy density and plant height. Remarkably, the PEnsemble 4 model achieves an accuracy rate of 91%. It improves the timing of yield predictions from the traditional reproductive stage (R6) to the earlier blister stage (R2), thus facilitating more timely decision-making in agricul tural practices. Additionally, the model also capabilities extend to the water stress, crop stress , and disease detection, enhancing overall agricultural management. By integrat ing multi-modal data and machine learning technologies, the PEnsemble 4 model offers an innovative and effective approach to maize yield prediction. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Internet of things |
| General subdivision | Agricultural applications |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Agriculture |
| General subdivision | Data processing |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Crop improvement |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Attaphongse Taparugssanagorn, |
| Relator term | Chairperson |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Vatcharaporn Esichaikul, |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Chaklam Silpasuwanchai, |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | National Science and Technology Development Agency (NSTDA),Thailand, |
| Relator term | Scholarship Donor |
| 810 2# - SERIES ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology. |
| Title of a work | Dissertations ; |
| Volume/sequential designation | no. ICT-24-02 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B23971">http://203.159.5.9/ait-thesis/detail.php?q=B23971</a> |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) | |
| a | .b12498695 |
| b | mnarc |
| c | a |
| 902 ## - LOCAL DATA ELEMENT B, LDB (RLIN) | |
| a | 260423 |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 260422 |
| First date, FD (RLIN) | m |
| -- | h |
| -- | a |
| -- | 0 |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnarc |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 67-Electronic Resource |
| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : - |
| CREATED | CREATED : 2026-07-04 |
| RECORD Id | RECORD # : i13595453 |
| LPATRON | LPATRON : 0 |
| LCHKIN | LCHKIN : - |
| RENEWALS | # RENEWALS : 0 |
| -- | # OVERDUE : 0 |
| -- | IUSE3 : 0 |
| -- | TOT CHKOUT : 0 |
| -- | TOT RENEW : 0 |
| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total checkouts | Full call number | Date last seen | Copy number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 18/08/2026 | AIT Diss. no.ICT-24-02 | 18/08/2026 | 1 | 18/08/2026 | 67-Electronic Resource |