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Enhancing Driver Safety: Integrating ECG and CAN-Bus Data for Accurate Drowsiness Detection
No full textDriver drowsiness is one of the main causes of serious traffic accidents and a significant risk factor, especially for long journeys and heavy vehicle drivers. To prevent drowsiness-related accidents, it is of great importance to develop accurate and reliable systems for the detection. This study makes an innovative contribution by proposing a hybrid system that uses both physiological data (ECG) and in-vehicle data (CAN-Bus) to detect driver drowsiness. Aim is to provide higher accuracy detection by combining two different data sources. ECG and CAN-Bus data were collected from real drivers under various environmental and traffic conditions, and these data were analyzed using machine learning algorithms. A three-class drowsiness detection model was developed and this model classified drivers into low, medium and high drowsiness levels. The results obtained showed that the model was successful in drowsiness detection with an accuracy rate of 85%. AThis rate offers a significant improvement compared to previous studies based on only ECG data. Developed system is designed for real-world driving environments and has the potential for industrial implementation, offering an impactful solution to increase driver safety and prevent drowsiness-related accidents
Birleşmiş Milletler Deniz Hukuku Sözleşmesi Madde 35 (c) Kapsamındaki Boğazlar (Türk Boğazları Hariç)
No full textBirleşmiş Milletler Deniz Hukuku Sözleşmesi (BMDHS)’ne göre, uluslararası seyrüseferde kullanılan boğazlardan temel geçiş rejimi, transit geçiş rejimi olarak belirlenmiştir. Ancak Sözleşmenin 35 (c) maddesi uyarınca, geçişlerin yürürlükte olan ve uzun süredir devam eden uluslararası sözleşmelerle tamamen veya kısmen düzenlendiği boğazlarda transit geçiş rejimi ve zararsız geçiş rejimi uygulanmayacaktır. Uluslararası sözleşmelerin önceliğini tanıyan bu hüküm, deniz hukukunun her zaman katı kurallarla değil, tarihsel birikimi ve devletler arasındaki çıkar dengeleri gözeterek şekillendiğini göstermektedir. Bu madde temelinde, kendi özel rejimlerini koruyan ve genel kurallardan sapan az sayıda boğazın varlığı dikkat çekmektedir. Bu çalışma, BMDHS’nin 35 (c) maddesi kapsamında bulunan Danimarka, Macellan ve Åland Boğazlarının hukukî statüsünü ve geçiş rejimlerini incelemekte ve hukuki statüsü tartışmalı olan Cebelitarık Boğazı’nı ele almaktadır
TIBBİ KÖTÜ UYGULAMALARDAN KAYNAKLANAN MADDİ ZARAR VE BU ZARARIN HESAPLANMASI
No full textMakalemizde tıbbi kötü uygulamalardan kaynaklanan maddi zararların sınıflandırılması, zarar kalemleri ve bu zararların hesaplanmasında kullanılan yöntemler ele alınmaktadır. Tıbbi uygulama hataları sonucu meydana gelen maddi zararlar, cenaze giderleri, tedavi giderleri, çalışma gücünün azalmasından veya yitirilmesinden doğan kayıplar ve destekten yoksun kalma nedeniyle uğranılan zararlar gibi çeşitli kalemler altında incelenmiştir. Bu zararların hesaplanmasında kullanılan yaşam tabloları ve aktüerya hesaplama yöntemleri detaylı olarak açıklanmış, yargı kararları ve doktrin ışığında bu konular kapsamlı bir şekilde değerlendirilmiştir. Tıbbi kötü uygulamalardan kaynaklanan maddi zararların hesaplanmasında kullanılan yöntemlerin etkinliği ve doğruluğu tartışılarak, bu alandaki uygulamaların geliştirilmesine yönelik öneriler sunulmuştur
Photoluminescence characteristics and Judd-Ofelt analysis of YBa3(BO3)3:Tb3+ phosphors co-doped with Li+, Na+, and K+
No full textThis study presents a systematic investigation of the photoluminescent properties of Tb3+-doped YBa3(BO3)(3) (YBBO) phosphors, synthesized via a microwave-assisted sol-gel combustion (MA-SG) method and co-doped with monovalent alkali ions (Li+, Na+, K+). Structural, vibrational, and morphological analyses were performed using XRD with Rietveld refinement, Raman and FTIR spectroscopy, and SEM-EDS. These analyses confirmed the successful incorporation of dopants without compromising the borate lattice. Photoluminescence (PL) measurements under near-UV excitation (377 nm) showed intense green emission attributed to the D-5(4) -> F-7(5) transition of Tb3+, with Li+ co-doping producing the greatest enhancement (similar to 2.7 x ) in emission intensity. Lifetime measurements revealed longer decay times with co-doping, suggesting reduced non-radiative relaxation processes. Judd-Ofelt (J-O) analysis confirmed strong radiative transitions and high internal quantum efficiency (eta approximate to 48.4 %). The internal quantum efficiency (IQE) of 48.4 % was estimated using Judd-Ofelt theory, which is based on radiative transition probabilities derived from emission spectra. This method, while theoretical, is widely accepted for powdered phosphors and provides insight into the intrinsic radiative efficiency of the activator ions. Although absolute quantum yield (QY) measurements are typically obtained using integrating sphere systems to account for all optical losses, in this study, such measurements were not performed. Nonetheless, the strong agreement between radiative parameters and observed photoluminescence behavior supports the reliability of the calculated efficiency. In this study, J-O parameters were derived from the integrated emission spectra of Tb3+ transitions, following an emission-based approach that has been increasingly employed for powdered phosphors due to its experimental feasibility. Colorimetric analysis using CIE chromaticity diagrams validated the tunable green emission behaviour of the phosphors. Minor deviations from ideal green were linked to background blue emission from the host matrix, a feature that may offer spectral advantages in multifunctional optical applications. Furthermore, the phosphor exhibited a rare negative thermal quenching (NTQ) behavior, maintaining or enhancing emission intensity up to 550 K, which is superior to many commercial green phosphors.These results highlight the crucial role of alkali ion co-doping in tuning the local crystal field, enhancing emission efficiency, and paving the way for the development of efficient green-emitting phosphors for solid-state lighting applications.Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia [PNURSP2025R16]; Scientific and Technological Research Council of Turkey [1001-223M036]We express our gratitude to the Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R16) , Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. The authors acknowledge grants from the Scientific and Technological Research Council of Turkey (TUBITAK, project number: 1001-223M036)
The effect of mobile augmented reality learning on type 2 diabetes patients' insulin application knowledge and skills
No full textBu çalışma tip 2 diyabet hastalarının insülin uygulamaları konusunda bilgi, becerilerinin arttırılması üzerine artırılmış gerçeklik ile insülin uygulamasının etkinliğinin belirlenmesi, hasta eğitiminden memnuniyet durumlarının saptanması ve iki stratejinin karşılaştırılması amacıyla gerçekleştirilmiştir. Ön-test ve son-test uygulama gruplu yarı deneysel bir çalışmadır. Çalışma 1 Kasım 2023 -31 Aralık 2024 tarihleri arasında İzmir Bakırçay Üniversitesi Çiğli Eğitim Araştırma Hastanesi Dahiliye servisinde yatan, araştırmaya katılmaya gönüllü olan yeni tanılı Tip 2 diyabetli hastalar (n:100) ile gerçekleştirildi. Çalışmanın verileri "Birey Tanılama Formu", "Bilgi Testi (Ön-test, Son-test)", "Hasta Eğitiminde Memnuniyet Ölçeği" ve "İnsulin Uygulama Becerisi Değerlendirme Kontrol Formu" ile toplandı. Her iki uygulama grubuna (Broşür ve MAG) eğitim öncesi eğitim ile ilgili bilgi verilip ön bilgi testi uygulandı. Her iki uygulama grubuna eğitim verildikten sonra son bilgi testi ve hasta eğitiminden memnuniyet ölçeği uygulandı. Son olarak her iki uygulama grubuna eğitimde öğrendiği insülin uygulama basamaklarını hasta kendi üzerinde gerçekleştirdi. Araştırmacı hastaları İnsulin "Uygulama Becerisi Değerlendirme Kontrol Formu" ile değerlendirdi. Uygulama bir (Broşür) ve iki (MAG) grubunun bilgi testinden elde edilen son-test bilgi testi toplam puanları arasında istatistiksel olarak anlamlı bir fark tespit edilmiştir (p<0,05). Uygulama bir ve iki gruplarında göre ön test ve son test bilgi testi toplam puanları arasında istatistiksel olarak anlamlı farklar belirlenmiştir (p<0,05). Tip 2 diyabetli hasta gruplarına göre İnsulin Uygulama Becerisi Değerlendirme puanları arasında istatistiksel olarak anlamlı bir fark belirlenmiştir (p<0,05). Uygulama iki grubunun puanları uygulama bir grubunun puanlarından yüksektir. Tip 2 diyabet hastaların Hasta Eğitiminden Memnuniyet ölçeği puan ortalamaları arasında istatistiksel olarak anlamlı bir fark tespit edilmiştir (p<0,05). Sonuç olarak, MAG eğitim materyali ile eğitim verilen hastaların diğer hasta grubuna göre insülin konusuna ilişkin bilgi, beceri ve hasta eğitiminde memnuniyet düzeyleri üzerinde etkili olduğu saptandı. Anahtar Sözcüler: Tip 2 diyabet, mobil artırılmış gerçeklik, insülin uygulaması, hasta eğitimi, hemşirelikThis study aimed to evaluate the effectiveness of augmented reality (AR) in insulin administration on enhancing the knowledge and skills of Type 2 diabetes patients, assess their satisfaction with patient education, and compare two different strategies. It is a quasi-experimental study with pre-test and post-test application groups. The study was conducted between November 1, 2023, and December 31, 2024, with newly diagnosed Type 2 diabetes patients (n=100) hospitalized in the Internal Medicine Department of İzmir Bakırçay University Çiğli Training and Research Hospital who volunteered to participate. Data were collected using the "Individual Identification Form," "Knowledge Test (Pre-Test, Post-Test)," "Patient Education Satisfaction Scale," and the "Insulin Administration Skill Evaluation Checklist." Both application groups (Brochure and AR) were provided with preliminary information about the training and took a pre-knowledge test before the training. After the training sessions, the post-knowledge test and the Patient Education Satisfaction Scale were administered to both groups. Finally, each patient performed the insulin administration steps they had learned during the training on themselves. The researcher evaluated the patients using the "Insulin Administration Skill Evaluation Checklist." A statistically significant difference was found between the total post-test knowledge test scores of the Brochure and AR groups (p<0.05). Statistically significant differences were also observed between the pre-test and post-test knowledge test scores within both groups (p<0.05). A statistically significant difference was identified in the Insulin Administration Skill Evaluation scores among the patient groups (p<0.05), with the AR group scoring higher than the Brochure group. Additionally, a statistically significant difference was noted in the mean scores of the Patient Education Satisfaction Scale between the two groups (p<0.05). In conclusion, it was determined that patients who received training using AR educational material showed greater improvement in knowledge, skills, and satisfaction with patient education on insulin administration compared to those trained with traditional methods. Keywords: Type 2 diabetes, mobile augmented reality, insulin administration, patient education, nursin
Optimising urban lighting efficiency with IoT and LoRaWAN integration in smart street lighting systems
No full textThe integration of the Internet of Things (IoT) into smart city frameworks ushers in new opportunities for merging and enhancing diverse services, enabling seamless connectivity across multiple application domains. This paper presents the LoRaWAN-IoT-SSLS, an advanced automated streetlight control system that leverages IoT technology to achieve substantial energy savings and minimise the need for manual intervention. By employing LoRaWAN as the sensor network backbone, the system effectively addresses challenges related to long-range data transmission in IoT applications. The setup integrates a programmed Arduino board with PIR and LDR sensors, a GPS module, a LoRa shield, and a LoRaWAN gateway. The system is powered by a monocrystalline solar panel with a solar charger shield and battery and utilises LED lights for illumination. These components collectively enable automated switching and adaptive brightness control based on real-time environmental conditions, optimising energy use and enhancing safety. The system's performance was validated across distances up to 1000 m, maintaining stable operation with SNR values ranging from 9.8 to 1.5 dB and reliable RSSI levels, demonstrating robust communication and monitoring capabilities. Real-time status updates are visualised through the TagoIO platform, allowing for continuous remote management. The deployment of LoRaWAN-IoT-SSLS has the potential to significantly reduce electricity consumption and CO2 emissions by harnessing renewable energy resources. By activating lighting only when pedestrians or vehicles are detected and dimming or turning off when no presence is sensed, the system demonstrates superior performance over conventional models. This scalable and secure solution lays the groundwork for future innovations in smart urban infrastructure, setting new benchmarks for energy-efficient city lighting. © 2025 Elsevier B.V., All rights reserved.Birmingham City University, BC
Measurement of the inclusive WZ production cross section in pp collisions at ?s=13.6 TeV
No full textThe inclusive WZ production cross section is measured in proton-proton collisions at a centre-of-mass energy of 13.6 TeV, using data collected during 2022 with the CMS detector, corresponding to an integrated luminosity of 34.7 fb(-1). The measurement uses multileptonic final states and a simultaneous likelihood fit to the number of events in four different lepton flavour categories: eee, ee mu, mu mu e, and mu mu mu. The selection is optimized to minimize the number of background events, and relies on an efficient prompt lepton discrimination strategy. The WZ production cross section is measured in a phase space defined within a 30 GeV window around the Z boson mass, as sigma(total) (pp -> WZ) = 55.2 +/- 1.2 (stat) +/- 1.2 (syst) +/- 0.8 (lumi) +/- 0.3 (theo) pb. In addition, the cross section is measured in a fiducial phase space closer to the detector-level requirements. All the measurements presented in this paper are in agreement with standard model predictions.FWF; FNRS; FWO (Belgium); CNPq; CAPES; FAPERJ; FAPERGS; FAPESP (Brazil); BNSF (Bulgaria); MoST; NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG [MoER TK202]; Academy of Finland; MEC; CEA; CNRS/IN2P3 (France); SRNSF; BMBF; DFG; HGF (Germany); NKFIH (Hungary); DAE; DST; IPM; SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE; UM (Malaysia); BUAP; CONACYT; UASLP-FAI (Mexico); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); NSTDA; TUBITAK; DOE; NSF; Marie-Curie programme; European Research Council; Horizon 2020 Grant [675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207]; COST Action [CA16108]; Leventis Foundation; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation; Science Committee [22rl-037]; Belgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); FWO (Belgium) under the Excellence of Science - EOS [30820817]; Beijing Municipal Science & Technology Commission [Z191100007219010]; Fundamental Research Funds for the Central Universities (China); Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; Shota Rustaveli National Science Foundation [FR-22-985]; Deutsche Forschungsgemeinschaft (DFG) [EXC 2121, 390833306, 400140256 - GRK2497]; Hellenic Foundation for Research and Innovation (HFRI) [2288]; Hungarian Academy of Sciences [K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64, 2021-4.1.2-NEMZ_KI]; Council of Science and Industrial Research, India - NextGenerationEU program (Italy); Latvian Council of Science; Ministry of Education and Science [2022/WK/14]; National Science Center [Opus 2021/41/B/ST2/01369, 2021/43/B/ST2/01552, CEECIND/01334/2018]; National Priorities Research Program by Qatar National Research Fund; ERDF a way of making Europe [MDM-2017-0765]; Programa Severo Ochoa del Principado de Asturias (Spain); National Science, Research and Innovation Fund via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation [B39G670016]; Kavli Foundation; Nvidia Corporation; SuperMicro Corporation; Welch Foundation [C-1845]; Weston Havens Foundation (U.S.A.)We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid and other centres for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LMTLT (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl-037 (Armenia); the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the Excellence of Science - EOS - be.h project n. 30820817; the Beijing Municipal Science & Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR-22-985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), among others, under Germany's Excellence Strategy - EXC 2121 Quantum Universe - 390833306, and under project number 400140256 - GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program - uNKP, the NKFIH research grants K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64, and 2021-4.1.2-NEMZ_KI (Hungary); the Council of Science and Industrial Research, India; ICSC - National Research Centre for High Performance Computing, Big Data and Quantum Computing and FAIR - Future Artificial Intelligence Research, funded by the NextGenerationEU program (Italy); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the FundacAo para a Ciencia e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MCIN/AEI/10.13039/501100011033, ERDF a way of making Europe, and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation, grant B39G670016 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.)
Satisfaction levels of patients with musculoskeletal problems treated with physical therapy modalities: A multi-center study
No full textObjectives: This study aims to assess patients' level of satisfaction with physical therapy modalities from different centers in T & uuml;rkiye. Patients and methods: In this cross-sectional study, a Patient Satisfaction Questionnaire in the Treatment with the Physical Therapy Modalities was created by the Turkish Society of Physical Medicine and Rehabilitation, the Physical Therapy Modalities Working Group and it was applied to a total of 2,466 patients (847 males, 1,619 females; mean age: 51.8 +/- 14.6 years; range, 18 to 90 years) from 13 different hospitals. The participants were selected from patients who were treated in the physical therapy and rehabilitation departments of nine universities and four training and research hospitals for musculoskeletal complaints. The questionnaire included questions assessing demographic data, disease characteristics and level of satisfaction with the treatment program. Consecutive patients that were enrolled in treatment programs for musculoskeletal problems were included in the study. Results: The cumulative rate of patients who were very satisfied and satisfied with these treatments was 54.1%. The higher the education level, the higher the satisfaction rate was. The satisfaction level of the currently employed was higher than that of retirees. The patients who were most satisfied with physical therapy were those who presented with cervical spinal complaints. The rate of patients who never received physical therapy before was 51.5%, indicating higher satisfaction levels. Outpatient physical therapy patients reported higher satisfaction rates than inpatients. The patients conveyed their satisfaction with the therapist performing the treatment and expressed their intention to choose physical therapy again, if necessary. Conclusion: Patients express high levels of satisfaction with physical therapy modalities, and they encounter minimal or no issues in practice
Design of a novel memtranstor emulator using CCIIs and experimental validation
No full textThis study introduces a new memtranstor emulator circuit using second-generation current conveyors (CCII), providing an alternative to the only existing memtranstor emulator circuit in the literature. The proposed circuit consists of three CCIIs, one analog multiplier (AD633), two grounded resistors, and three grounded capacitors. The design is implemented using 180 nm CMOS technology, and its functionality is validated through PSPICE simulations. The circuit's behavior is analyzed under various conditions including pinched hysteresis loops, Monte Carlo analysis, memory effect simulations, and temperature variation tests, all of which confirm its proper operation. Additionally, the circuit can be easily adapted between incremental and decremental memory emulators, demonstrating its versatility for various applications. The proposed emulator has been further validated through experimental implementation, confirming its feasibility for practical applications. A memtranstor-based chaotic oscillator is presented as an application example. Compared to the existing design in the literature, the proposed emulator offers several key advantages: It employs fewer active and passive components, leading to a simpler structure with the potential for more compact implementation. The absence of operational amplifiers (op-amps) improves bandwidth performance by eliminating the fixed gain-bandwidth product limitation, enabling higher gain levels at broader bandwidths. Additionally, the use of low-power CMOS parameters potentially allows for lower supply voltages, which, along with fewer components, can significantly reduce power consumption
Artificial Intelligence in Forestry: A Comprehensive Analysis of Current Applications and Future Perspectives
No full textThis study systematically analyzes artificial intelligence (AI) applications in forestry management, exploring current implementations, challenges, and future perspectives. A review of 580 articles from Web of Science (211) and Scopus (369) databases (2021-2025) identifies key themes where AI is transforming forestry practices. Forest Monitoring and Management Systems (30.4%) and Digital Transformation (23.6%) dominate current research, followed by Resource Optimization (17.1%) and Biodiversity Conservation (14.6%). Significant opportunities are noted in productivity enhancement, risk analysis, biodiversity conservation, and carbon management through AI. However, challenges such as data quality, resource constraints, operational complexities, and regulatory requirements remain. Emerging trends like human-centered AI, digital twins, and integrated sensor networks show promise. This analysis offers valuable insights for forestry professionals, researchers, and policymakers, providing a framework to understand AI's potential and limitations while emphasizing balanced integration for environmental sustainability and operational efficiency