An improved adaptive data rate algorithm of LoRaWAN for agricultural mobile sensor nodes
•The number of packets is dynamically adjusted based on the moving speed of nodes.•Time on Air (ToA) is used as a selection criterion for modulation parameters.•Distance, moving speed and SNR are used to determine the network margin. Wireless sensor network (WSN) is an important research area in sma...
Saved in:
| Published in | Computers and electronics in agriculture Vol. 219; p. 108773 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.04.2024
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 0168-1699 1872-7107 |
| DOI | 10.1016/j.compag.2024.108773 |
Cover
| Abstract | •The number of packets is dynamically adjusted based on the moving speed of nodes.•Time on Air (ToA) is used as a selection criterion for modulation parameters.•Distance, moving speed and SNR are used to determine the network margin.
Wireless sensor network (WSN) is an important research area in smart agriculture. As an emerging technology, LoRa is used for communication between wireless sensor nodes. When LoRa is used as a mobile terminal node (mobile robot, drone, etc.), the Quality of Service (QoS) of LoRa network will be greatly reduced, which will have an impact on the quantitative decision-making and intelligent control in the future. Therefore, a novel Adaptive Data Rate (ADR) algorithm for agricultural mobile sensor nodes is proposed in this paper. The channel condition changes are effectively sensed based on three LoRa signal characteristics of SNR, RSSI, and frequency offset. It could respond quickly to the complex and changeable radio channel environment, and configured the modulation parameters dynamically and accurately. The Mobile LoRaSim tool and Arduino + SX1278 hardware platform were adopted for evaluation and analysis. The results showed that compared with the standard ADR algorithm and the Blind ADR algorithm, the data extraction rate of the Mobile ADR algorithm was increased by 15 %, the data collision rate was reduced by 45 %, the network energy consumption was reduced by 8 %, and the time on air was reduced by 50 %. The proposed algorithm improves the adaptability and robustness in terms of QoS of LoRaWAN networks. |
|---|---|
| AbstractList | •The number of packets is dynamically adjusted based on the moving speed of nodes.•Time on Air (ToA) is used as a selection criterion for modulation parameters.•Distance, moving speed and SNR are used to determine the network margin.
Wireless sensor network (WSN) is an important research area in smart agriculture. As an emerging technology, LoRa is used for communication between wireless sensor nodes. When LoRa is used as a mobile terminal node (mobile robot, drone, etc.), the Quality of Service (QoS) of LoRa network will be greatly reduced, which will have an impact on the quantitative decision-making and intelligent control in the future. Therefore, a novel Adaptive Data Rate (ADR) algorithm for agricultural mobile sensor nodes is proposed in this paper. The channel condition changes are effectively sensed based on three LoRa signal characteristics of SNR, RSSI, and frequency offset. It could respond quickly to the complex and changeable radio channel environment, and configured the modulation parameters dynamically and accurately. The Mobile LoRaSim tool and Arduino + SX1278 hardware platform were adopted for evaluation and analysis. The results showed that compared with the standard ADR algorithm and the Blind ADR algorithm, the data extraction rate of the Mobile ADR algorithm was increased by 15 %, the data collision rate was reduced by 45 %, the network energy consumption was reduced by 8 %, and the time on air was reduced by 50 %. The proposed algorithm improves the adaptability and robustness in terms of QoS of LoRaWAN networks. Wireless sensor network (WSN) is an important research area in smart agriculture. As an emerging technology, LoRa is used for communication between wireless sensor nodes. When LoRa is used as a mobile terminal node (mobile robot, drone, etc.), the Quality of Service (QoS) of LoRa network will be greatly reduced, which will have an impact on the quantitative decision-making and intelligent control in the future. Therefore, a novel Adaptive Data Rate (ADR) algorithm for agricultural mobile sensor nodes is proposed in this paper. The channel condition changes are effectively sensed based on three LoRa signal characteristics of SNR, RSSI, and frequency offset. It could respond quickly to the complex and changeable radio channel environment, and configured the modulation parameters dynamically and accurately. The Mobile LoRaSim tool and Arduino + SX1278 hardware platform were adopted for evaluation and analysis. The results showed that compared with the standard ADR algorithm and the Blind ADR algorithm, the data extraction rate of the Mobile ADR algorithm was increased by 15 %, the data collision rate was reduced by 45 %, the network energy consumption was reduced by 8 %, and the time on air was reduced by 50 %. The proposed algorithm improves the adaptability and robustness in terms of QoS of LoRaWAN networks. |
| ArticleNumber | 108773 |
| Author | Li, Hongbo Liao, Jianxin Zhang, Yu Zhang, Xihai Wang, Hao |
| Author_xml | – sequence: 1 givenname: Hao surname: Wang fullname: Wang, Hao organization: School of Electrical and Information, Northeast Agricultural University, Harbin 150030, China – sequence: 2 givenname: Xihai surname: Zhang fullname: Zhang, Xihai email: xhzhang@neau.edu.cn organization: School of Electrical and Information, Northeast Agricultural University, Harbin 150030, China – sequence: 3 givenname: Jianxin surname: Liao fullname: Liao, Jianxin organization: School of Electrical and Information, Northeast Agricultural University, Harbin 150030, China – sequence: 4 givenname: Yu surname: Zhang fullname: Zhang, Yu email: zhangyu1900@neau.edu.cn organization: School of Electrical and Information, Northeast Agricultural University, Harbin 150030, China – sequence: 5 givenname: Hongbo surname: Li fullname: Li, Hongbo organization: School of Electrical and Information, Northeast Agricultural University, Harbin 150030, China |
| BookMark | eNqFkE9LAzEQxYNUsK1-Aw85etma7G67iQehFP9BURBFb2GazNaU3U1N0oLf3pT15EFPw8y89-D9RmTQuQ4JOedswhmfXW4m2rVbWE9ylpfpJKqqOCJDLqo8qzirBmSYZCLjMylPyCiEDUu7FNWQvM87atutd3s0FAxso90jNRCBeohIoVk7b-NHS11Nl-4Z3uaPtHaewtpbvWvizkNDW7eyDdKAXUivzhkMp-S4hibg2c8ck9fbm5fFfbZ8untYzJeZLgoZM14yyXKYcpDcVAZyqAVjBlHWBRihYbbiNTKsgUmTtNyspihWZWmM4BJ4MSYXfW7q8LnDEFVrg8amgQ7dLqiCT4tZqitkkpa9VHsXgsdabb1twX8pztQBpNqoHqQ6gFQ9yGS7-mXTNkK0rosebPOf-bo3Y2Kwt-hV0BY7jcZ61FEZZ_8O-AaL6JRI |
| CitedBy_id | crossref_primary_10_1007_s11227_024_06846_8 |
| Cites_doi | 10.1109/MCOM.2017.1600613 10.1109/JIOT.2018.2883728 10.1016/j.compag.2022.106770 10.3390/s20185044 10.1177/1550147717699412 10.1109/JIOT.2018.2847702 10.1016/j.compag.2019.105169 10.1109/JIOT.2021.3118051 10.1016/j.simpat.2021.102388 10.1109/COMST.2017.2652320 10.1016/j.icte.2021.12.013 10.3390/s20226466 10.1016/j.compag.2023.108007 10.1109/NOMS.2018.8406255 10.1109/ACCESS.2018.2844405 10.1016/j.compeleceng.2021.106982 10.1109/JIOT.2020.3020189 10.1016/j.iot.2020.100176 10.1109/OJIES.2023.3329021 |
| ContentType | Journal Article |
| Copyright | 2024 Elsevier B.V. |
| Copyright_xml | – notice: 2024 Elsevier B.V. |
| DBID | AAYXX CITATION 7S9 L.6 |
| DOI | 10.1016/j.compag.2024.108773 |
| DatabaseName | CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitle | CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | AGRICOLA |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Agriculture |
| EISSN | 1872-7107 |
| ExternalDocumentID | 10_1016_j_compag_2024_108773 S0168169924001649 |
| GroupedDBID | --K --M .DC .~1 0R~ 1B1 1RT 1~. 1~5 29F 4.4 457 4G. 5GY 5VS 6J9 7-5 71M 8P~ 9JM 9JN AABVA AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALCJ AALRI AAOAW AAQFI AAQXK AATLK AAXUO AAYFN ABBOA ABBQC ABFNM ABFRF ABGRD ABJNI ABKYH ABLVK ABMAC ABMZM ABRWV ABXDB ABYKQ ACDAQ ACGFO ACGFS ACIUM ACIWK ACNNM ACRLP ACZNC ADBBV ADEZE ADJOM ADMUD ADQTV AEBSH AEFWE AEKER AENEX AEQOU AESVU AEXOQ AFKWA AFTJW AFXIZ AGHFR AGUBO AGYEJ AHHHB AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV AJRQY AKRWK ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ANZVX AOUOD ASPBG AVWKF AXJTR AZFZN BKOJK BLXMC BNPGV CBWCG CS3 DU5 EBS EFJIC EJD EO8 EO9 EP2 EP3 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA GBOLZ HLV HLZ HVGLF HZ~ IHE J1W KOM LCYCR LG9 LW9 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. PQQKQ Q38 QYZTP R2- RIG ROL RPZ SAB SBC SDF SDG SES SEW SNL SPC SPCBC SSA SSH SSV SSZ T5K UHS UNMZH WUQ Y6R ~G- ~KM AAHBH AATTM AAXKI AAYWO AAYXX ABWVN ACIEU ACLOT ACMHX ACRPL ACVFH ADCNI ADNMO ADSLC AEIPS AEUPX AFJKZ AFPUW AGQPQ AGWPP AIGII AIIUN AKBMS AKYEP ANKPU APXCP CITATION EFKBS EFLBG ~HD 7S9 L.6 |
| ID | FETCH-LOGICAL-c339t-140902a51a91d7da2af800dee9f3ad8ca6b1fe0efa09d4091db5e8b44dd819a13 |
| IEDL.DBID | .~1 |
| ISSN | 0168-1699 |
| IngestDate | Mon Sep 29 01:58:45 EDT 2025 Thu Apr 24 22:54:01 EDT 2025 Thu Oct 02 04:27:49 EDT 2025 Sat Apr 06 16:24:41 EDT 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | LoRaSim WSN QoS LoRaWAN Mobile ADR |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c339t-140902a51a91d7da2af800dee9f3ad8ca6b1fe0efa09d4091db5e8b44dd819a13 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| PQID | 3153600189 |
| PQPubID | 24069 |
| ParticipantIDs | proquest_miscellaneous_3153600189 crossref_primary_10_1016_j_compag_2024_108773 crossref_citationtrail_10_1016_j_compag_2024_108773 elsevier_sciencedirect_doi_10_1016_j_compag_2024_108773 |
| PublicationCentury | 2000 |
| PublicationDate | April 2024 2024-04-00 20240401 |
| PublicationDateYYYYMMDD | 2024-04-01 |
| PublicationDate_xml | – month: 04 year: 2024 text: April 2024 |
| PublicationDecade | 2020 |
| PublicationTitle | Computers and electronics in agriculture |
| PublicationYear | 2024 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Adelantado, Vilajosana, Tuset-Peiro, Martinez, MeliaSegui, Watteyne (b0005) 2017; 55 Farhad, Pyun (b0040) 2022 Wang (b0105) 2023; 211 Petajajarvi, J., Mikhaylov, K., Pettissalo, M., Janhunen, J., Iinatti, J. Performance of a low-power wide-area network based on LoRa technology: Doppler robustness, scalability, and coverage, International Journal of Distributed Sensor Networks, vol. 13, no. 3, 2017. 10.1177/1550147717699412. Raza, Kulkarni, Sooriyabandara (b0095) 2017; 19 Kufakunesu, Hancke, Abu-Mahfouz (b0060) 2020; 20 Deng, Zuo, Wen, Wu (b0035) 2020; 169 Marini, Cerroni, Buratti (b0070) 2021; 8 Zhang, X., Qiao, Y., Meng, F., Fan, C., Zhang, M. Identification of maize leaf diseases using improved deep convolutional neural networks, IEEE Access, vol. 6, pp. 30 370–30 377, 2018. 10.1109/ACCESS.2018.2844405. Farhad, Kim, Subedi, Pyun (b0045) 2020; 20 Ikpehai, Adebisi, Rabie, Anoh, Ande, Hammoudeh, Gacanin, Mbanaso (b0050) 2019; 6 Wang (b0110) 2023; 4 Chou, Mo, Su, Chang, Chen, Tang, Yu (b0020) 2017 Slabicki, M., Premsankar, G., Di Francesco, M. Adaptive configuration of lora networks for dense iot deployments, in NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, pp. 1–9, 2018. 10.1109/NOMS.2018.8406255. Moiroux-Arvis, Cariou, Chanet (b0075) 2022; 194 Cicioğlu, Çalhan (b0025) 2021; 90 Mroue, H., et al., LoRa plus: an extension of LoRaWAN protocol to reduce infrastructure costs by improving the Quality of Service, Internet of Things, vol. 9, no. 100176, 2020. 10.1016/j.iot.2020.100176. Benkahla, Tounsi, Song, Frikha (b0015) 2021 Delafontaine, Schiano, Cocco, Rusu, Floreano (b0030) 2020 Jiang, Yang, Chen, Liao, Song, Zhang (b0055) 2022; 9 Moysiadis, Lagkas, Argyriou, Sarigiannidis, Moscholios, Sarigiannidis (b0080) 2021; 113 Benkahla, Tounsi, Song, Frikha (b0010) 2019 Zhang, Zhang, Meng, Qiao, Xu, Hour (b0120) 2019; 6 Magno, Rickli, Quack, Brunecker, Benini (b0065) 2018 Delafontaine (10.1016/j.compag.2024.108773_b0030) 2020 10.1016/j.compag.2024.108773_b0115 Zhang (10.1016/j.compag.2024.108773_b0120) 2019; 6 Deng (10.1016/j.compag.2024.108773_b0035) 2020; 169 Farhad (10.1016/j.compag.2024.108773_b0045) 2020; 20 10.1016/j.compag.2024.108773_b0100 Magno (10.1016/j.compag.2024.108773_b0065) 2018 Raza (10.1016/j.compag.2024.108773_b0095) 2017; 19 Kufakunesu (10.1016/j.compag.2024.108773_b0060) 2020; 20 Moiroux-Arvis (10.1016/j.compag.2024.108773_b0075) 2022; 194 Benkahla (10.1016/j.compag.2024.108773_b0010) 2019 Farhad (10.1016/j.compag.2024.108773_b0040) 2022 Chou (10.1016/j.compag.2024.108773_b0020) 2017 Wang (10.1016/j.compag.2024.108773_b0110) 2023; 4 Adelantado (10.1016/j.compag.2024.108773_b0005) 2017; 55 Cicioğlu (10.1016/j.compag.2024.108773_b0025) 2021; 90 Wang (10.1016/j.compag.2024.108773_b0105) 2023; 211 Ikpehai (10.1016/j.compag.2024.108773_b0050) 2019; 6 Benkahla (10.1016/j.compag.2024.108773_b0015) 2021 Jiang (10.1016/j.compag.2024.108773_b0055) 2022; 9 10.1016/j.compag.2024.108773_b0085 Marini (10.1016/j.compag.2024.108773_b0070) 2021; 8 10.1016/j.compag.2024.108773_b0090 Moysiadis (10.1016/j.compag.2024.108773_b0080) 2021; 113 |
| References_xml | – reference: Petajajarvi, J., Mikhaylov, K., Pettissalo, M., Janhunen, J., Iinatti, J. Performance of a low-power wide-area network based on LoRa technology: Doppler robustness, scalability, and coverage, International Journal of Distributed Sensor Networks, vol. 13, no. 3, 2017. 10.1177/1550147717699412. – reference: Slabicki, M., Premsankar, G., Di Francesco, M. Adaptive configuration of lora networks for dense iot deployments, in NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, pp. 1–9, 2018. 10.1109/NOMS.2018.8406255. – volume: 194 year: 2022 ident: b0075 article-title: Evaluation of LoRa technology in 433-MHz and 868-MHz for underground to aboveground data transmission publication-title: Comput. Electron. Agric. – volume: 6 start-page: 590 year: 2019 end-page: 598 ident: b0120 article-title: A low-power wide-area network information monitoring system by combining Nb-IOT and Lora publication-title: IEEE Internet Things J. – volume: 169 year: 2020 ident: b0035 article-title: Novel soil environment monitoring system based on RFID sensor and LoRa publication-title: Comput. Electron. Agric. – volume: 113 year: 2021 ident: b0080 article-title: Extending adr mechanism for lora enabled mobile end-devices publication-title: Simulation Modelling Practice and Theory – reference: Mroue, H., et al., LoRa plus: an extension of LoRaWAN protocol to reduce infrastructure costs by improving the Quality of Service, Internet of Things, vol. 9, no. 100176, 2020. 10.1016/j.iot.2020.100176. – volume: 20 start-page: 6466 year: 2020 ident: b0045 article-title: Enhanced lorawan adaptive data rate for mobile internet of things devices publication-title: Sensors – volume: 90 year: 2021 ident: b0025 article-title: Smart agriculture with internet of things in cornfields publication-title: Comput. Electr. Eng. – volume: 9 start-page: 8989 year: 2022 end-page: 9001 ident: b0055 article-title: A new-dynamic adaptive data rate algorithm of loRaWAN in harsh environment publication-title: IEEE Internet Things J. – start-page: 789 year: 2017 end-page: 791 ident: b0020 article-title: i-car system: a lora-based low power wide area networks vehicle diagnostic system for driving safety publication-title: In 2017 International Conference on Applied System Innovation (ICASI) – volume: 20 start-page: 5044 year: 2020 ident: b0060 article-title: A survey on adaptive data rate optimization in lorawan: recent solutions and major challenges publication-title: Sensors – year: 2022 ident: b0040 article-title: Hadr: a hybrid adaptive data rate in lorawan for internet of things publication-title: ICT Express – volume: 6 start-page: 2225 year: 2019 end-page: 2240 ident: b0050 article-title: Low-power wide area network technologies for internet-of-things: a comparative review publication-title: IEEE Internet Things J. – start-page: 160 year: 2018 end-page: 161 ident: b0065 article-title: Poster abstract: combining lora and rtk to achieve a high precision selfsustaining geo-localization system publication-title: In 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) – start-page: 1 year: 2019 end-page: 6 ident: b0010 article-title: Enhanced adr for lorawan networks with mobility publication-title: In 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC) – start-page: 86 year: 2021 end-page: 91 ident: b0015 article-title: Vhmm-based e-adr for lorawan networks with unknown mobility patterns publication-title: In 2021 International Wireless Communications and Mobile Computing (IWCMC) – reference: Zhang, X., Qiao, Y., Meng, F., Fan, C., Zhang, M. Identification of maize leaf diseases using improved deep convolutional neural networks, IEEE Access, vol. 6, pp. 30 370–30 377, 2018. 10.1109/ACCESS.2018.2844405. – volume: 4 start-page: 476 year: 2023 end-page: 485 ident: b0110 article-title: An energy-saving LoRa linear network system with adaptive transmission parameter publication-title: IEEE Open Journal of the Industrial Electronics Society – volume: 8 start-page: 2670 year: 2021 end-page: 2680 ident: b0070 article-title: A novel collision-aware adaptive data rate algorithm for lorawan networks publication-title: IEEE Internet Things J. – volume: 211 year: 2023 ident: b0105 article-title: A feedback control method for plant factory environment based on photosynthetic rate prediction model publication-title: Comput. Electron. Agric. – volume: 19 start-page: 855 year: 2017 end-page: 873 ident: b0095 article-title: Low power wide area networks: an overview publication-title: IEEE Commun. Surv. Tutorials – volume: 55 start-page: 34 year: 2017 end-page: 40 ident: b0005 article-title: Understanding the limits of lorawan publication-title: IEEE Commun. Mag. – start-page: 286 year: 2020 end-page: 292 ident: b0030 article-title: Drone-aided localization in lora iot networks publication-title: In 2020 IEEE International Conference on Robotics and Automation (ICRA) – volume: 55 start-page: 34 issue: 9 year: 2017 ident: 10.1016/j.compag.2024.108773_b0005 article-title: Understanding the limits of lorawan publication-title: IEEE Commun. Mag. doi: 10.1109/MCOM.2017.1600613 – start-page: 789 year: 2017 ident: 10.1016/j.compag.2024.108773_b0020 article-title: i-car system: a lora-based low power wide area networks vehicle diagnostic system for driving safety – volume: 6 start-page: 2225 issue: 2 year: 2019 ident: 10.1016/j.compag.2024.108773_b0050 article-title: Low-power wide area network technologies for internet-of-things: a comparative review publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2018.2883728 – volume: 194 year: 2022 ident: 10.1016/j.compag.2024.108773_b0075 article-title: Evaluation of LoRa technology in 433-MHz and 868-MHz for underground to aboveground data transmission publication-title: Comput. Electron. Agric. doi: 10.1016/j.compag.2022.106770 – start-page: 160 year: 2018 ident: 10.1016/j.compag.2024.108773_b0065 article-title: Poster abstract: combining lora and rtk to achieve a high precision selfsustaining geo-localization system – volume: 20 start-page: 5044 issue: 18 year: 2020 ident: 10.1016/j.compag.2024.108773_b0060 article-title: A survey on adaptive data rate optimization in lorawan: recent solutions and major challenges publication-title: Sensors doi: 10.3390/s20185044 – ident: 10.1016/j.compag.2024.108773_b0090 doi: 10.1177/1550147717699412 – volume: 6 start-page: 590 issue: 1 year: 2019 ident: 10.1016/j.compag.2024.108773_b0120 article-title: A low-power wide-area network information monitoring system by combining Nb-IOT and Lora publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2018.2847702 – volume: 169 year: 2020 ident: 10.1016/j.compag.2024.108773_b0035 article-title: Novel soil environment monitoring system based on RFID sensor and LoRa publication-title: Comput. Electron. Agric. doi: 10.1016/j.compag.2019.105169 – volume: 9 start-page: 8989 issue: 11 year: 2022 ident: 10.1016/j.compag.2024.108773_b0055 article-title: A new-dynamic adaptive data rate algorithm of loRaWAN in harsh environment publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2021.3118051 – volume: 113 year: 2021 ident: 10.1016/j.compag.2024.108773_b0080 article-title: Extending adr mechanism for lora enabled mobile end-devices publication-title: Simulation Modelling Practice and Theory doi: 10.1016/j.simpat.2021.102388 – volume: 19 start-page: 855 issue: 2 year: 2017 ident: 10.1016/j.compag.2024.108773_b0095 article-title: Low power wide area networks: an overview publication-title: IEEE Commun. Surv. Tutorials doi: 10.1109/COMST.2017.2652320 – year: 2022 ident: 10.1016/j.compag.2024.108773_b0040 article-title: Hadr: a hybrid adaptive data rate in lorawan for internet of things publication-title: ICT Express doi: 10.1016/j.icte.2021.12.013 – volume: 20 start-page: 6466 issue: 22 year: 2020 ident: 10.1016/j.compag.2024.108773_b0045 article-title: Enhanced lorawan adaptive data rate for mobile internet of things devices publication-title: Sensors doi: 10.3390/s20226466 – start-page: 1 year: 2019 ident: 10.1016/j.compag.2024.108773_b0010 article-title: Enhanced adr for lorawan networks with mobility – volume: 211 year: 2023 ident: 10.1016/j.compag.2024.108773_b0105 article-title: A feedback control method for plant factory environment based on photosynthetic rate prediction model publication-title: Comput. Electron. Agric. doi: 10.1016/j.compag.2023.108007 – ident: 10.1016/j.compag.2024.108773_b0100 doi: 10.1109/NOMS.2018.8406255 – ident: 10.1016/j.compag.2024.108773_b0115 doi: 10.1109/ACCESS.2018.2844405 – volume: 90 year: 2021 ident: 10.1016/j.compag.2024.108773_b0025 article-title: Smart agriculture with internet of things in cornfields publication-title: Comput. Electr. Eng. doi: 10.1016/j.compeleceng.2021.106982 – volume: 8 start-page: 2670 issue: 4 year: 2021 ident: 10.1016/j.compag.2024.108773_b0070 article-title: A novel collision-aware adaptive data rate algorithm for lorawan networks publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2020.3020189 – start-page: 86 year: 2021 ident: 10.1016/j.compag.2024.108773_b0015 article-title: Vhmm-based e-adr for lorawan networks with unknown mobility patterns – ident: 10.1016/j.compag.2024.108773_b0085 doi: 10.1016/j.iot.2020.100176 – start-page: 286 year: 2020 ident: 10.1016/j.compag.2024.108773_b0030 article-title: Drone-aided localization in lora iot networks – volume: 4 start-page: 476 year: 2023 ident: 10.1016/j.compag.2024.108773_b0110 article-title: An energy-saving LoRa linear network system with adaptive transmission parameter publication-title: IEEE Open Journal of the Industrial Electronics Society doi: 10.1109/OJIES.2023.3329021 |
| SSID | ssj0016987 |
| Score | 2.4438412 |
| Snippet | •The number of packets is dynamically adjusted based on the moving speed of nodes.•Time on Air (ToA) is used as a selection criterion for modulation... Wireless sensor network (WSN) is an important research area in smart agriculture. As an emerging technology, LoRa is used for communication between wireless... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 108773 |
| SubjectTerms | agriculture air algorithms electronics energy LoRaSim LoRaWAN Mobile ADR QoS radio WSN |
| Title | An improved adaptive data rate algorithm of LoRaWAN for agricultural mobile sensor nodes |
| URI | https://dx.doi.org/10.1016/j.compag.2024.108773 https://www.proquest.com/docview/3153600189 |
| Volume | 219 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Baden-Württemberg Complete Freedom Collection (Elsevier) customDbUrl: eissn: 1872-7107 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016987 issn: 0168-1699 databaseCode: GBLVA dateStart: 20110101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier ScienceDirect customDbUrl: eissn: 1872-7107 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016987 issn: 0168-1699 databaseCode: .~1 dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals [SCFCJ] customDbUrl: eissn: 1872-7107 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016987 issn: 0168-1699 databaseCode: AIKHN dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Science Direct customDbUrl: eissn: 1872-7107 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016987 issn: 0168-1699 databaseCode: ACRLP dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVLSH databaseName: Elsevier Journals customDbUrl: mediaType: online eissn: 1872-7107 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016987 issn: 0168-1699 databaseCode: AKRWK dateStart: 19851001 isFulltext: true providerName: Library Specific Holdings |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3NT9swFLdQuWwHxDbQChsy0q6hce3G8TGqVnUDehig9WY9f6QUtUnVjyt_O8_5qMQkhLRjkmfHenZ-_tn5vWdCfigQvG-tiZhMbSSE4BH4XEXGChknPmcAYUP_dpKMH8Tv6WB6QIZtLEyQVTbYX2N6hdbNnV7jzd5qPu_dIVlJWaJUUEEi6Q9BfELIcIrB1fNe5oEGaR0yneBqCa3b8LlK41XpvGe4SuyLILaTkr81Pf0D1NXsMzomRw1tpFndsk_kwBefycdstm5SZ_gvZJoVdF5tEXhHwcEqABkNClAa0kFQWMzK9Xz7uKRlTm_KP_A3m1CkrBT2teAblqVBnKAbXN3io6J0fnNCHkY_74fjqDk3IbKcq20UcljFfRgwUMxJB33IkRY671XOwaUWEsNyH_scYuXQljkz8KkRwjnkB8D4KekUZeG_EpoCj4VJvUFr7DwJMWK7k4rxgc2ti7uEt-7StkkqHs62WOhWPfakayfr4GRdO7lLon2pVZ1U4x172faEfjU4NOL-OyUv247T-N2EnyFQ-HK30RyhPpC9VJ39d-3n5EO4qoU830hnu97578hRtuaiGoQX5DD7dT2evADaxufE |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3NT9swFLeAHWCHifGhsbHNSFxD49iJ42OFQN1WehggerOeP1I6laRqy5W_ned8VGISQuIaPzvRs_Pz79k_PxNyqkDwxFoTMZnbSAjBI_CFiowVMs58wQDCgv7VKBvcit_jdLxBzruzMEFW2WJ_g-k1WrdPeq03e_PptHeNZCVnmVJBBYmkX22SDyJNZIjAzp7WOg-0yJsz0xmGS2jenZ-rRV610HuCYWIigtpOSv7a_PQfUtfTz-Uu-dTyRtpvPu0z2fDlHvnYnyza3Bl-n4z7JZ3WawTeUXAwD0hGgwSUhnwQFGaTajFd3T_QqqDD6i_c9UcUOSuFdSv4hofKIFDQJYa3WFRWzi8PyO3lxc35IGovTogs52oVhSRWcQIpA8WcdJBAgbzQea8KDi63kBlW-NgXECuHtsyZ1OdGCOeQIADjh2SrrEr_hdAceCxM7g1aY-9JiBHcnVSMp7awLj4ivHOXtm1W8XC5xUx38rF_unGyDk7WjZOPSLSuNW-yarxhL7ue0C9Gh0bgf6PmSddxGn-csBsCpa8el5oj1ge2l6uv7279J9ke3FwN9fDX6M83shNKGlXPMdlaLR79dyQsK_OjHpDPR9PpWQ |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=An+improved+adaptive+data+rate+algorithm+of+LoRaWAN+for+agricultural+mobile+sensor+nodes&rft.jtitle=Computers+and+electronics+in+agriculture&rft.au=Wang%2C+Hao&rft.au=Zhang%2C+Xihai&rft.au=Liao%2C+Jianxin&rft.au=Zhang%2C+Yu&rft.date=2024-04-01&rft.pub=Elsevier+B.V&rft.issn=0168-1699&rft.eissn=1872-7107&rft.volume=219&rft_id=info:doi/10.1016%2Fj.compag.2024.108773&rft.externalDocID=S0168169924001649 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0168-1699&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0168-1699&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0168-1699&client=summon |