research-article

Experience: adopting indoor outdoor detection in on-demand food delivery business

Authors:

Tian HeAuthors Info & Claims

MobiCom '22: Proceedings of the 28th Annual International Conference on Mobile Computing And Networking

Pages 94 - 105

https://doi.org/10.1145/3495243.3517023

Published: 14 October 2022 Publication History

Abstract

This paper presents our experience in adopting recent research results of mobile phone based indoor/outdoor detection (IODetector) to support the real world business of on-demand food delivery. The real world deployment of the adopted IODetector involves three phases spanning 20 months, during which the deployment scales from a feasibility study across a few areas of interest to a city-wide trial in Shanghai, and eventually to nationwide deployment over 367 cities in China. Iterative development has been performed throughout different deployment phases to excel the IODetector. Large scale evaluation and comparative A/B testing suggest key value of adopting indoor/outdoor detection in the real world business. We also present the lessons learned from the deployment experience including real world know-hows, practical limits and constraints, as well as discussions on design alternatives. We believe this paper provides insights to guide future efforts in translating research results to industry adoptions.

References

[1]

2021. Beidou Navigation Satellite System. http://en.beidou.gov.cn/. [Online; accessed 19-Aug-2021].

[2]

2021. Ele.me courier privacy policy. https://logisticsapp.ele.me/static/zb-h5/dist/protocol.html#/?type=secret&opt_type=0. [Online; accessed 19-Aug-2021].

[3]

2021. Galileo Positioning System. https://www.gsc-europa.eu/. [Online; accessed 19-Aug-2021].

[4]

2021. GLObal NAvigation Satellite System. https://www.glonass-iac.ru/en/. [Online; accessed 19-Aug-2021].

[5]

2021. The Global Positioning System. https://www.gps.gov/systems/gps/. [Online; accessed 19-Aug-2021].

[6]

Mohamed S. Abdelfattah, undefinedukasz Dudziak, Thomas Chau, Royson Lee, Hyeji Kim, and Nicholas D. Lane. 2020. Best of Both Worlds: AutoML Codesign of a CNN and Its Hardware Accelerator. In Proceedings of the 57th ACM/EDAC/IEEE Design Automation Conference (DAC '20). Article 192, 6 pages.

[7]

Özgü Alay, Andra Lutu, Miguel Peón-Quirós, Vincenzo Mancuso, Thomas Hirsch, Kristian Evensen, Audun Hansen, Stefan Alfredsson, Jonas Karlsson, Anna Brunstrom, Ali Safari Khatouni, Marco Mellia, and Marco Ajmone Marsan. 2017. Experience: An Open Platform for Experimentation with Commercial Mobile Broadband Networks. In Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking (MobiCom '17). 70--78.

Digital Library

[8]

Mohsen Ali, Tamer ElBatt, and Moustafa Youssef. 2018. SenseIO: Realistic Ubiquitous Indoor Outdoor Detection System Using Smartphones. IEEE Sensors Journal 18, 9 (2018), 3684--3693.

[9]

Roshan Ayyalasomayajula, Aditya Arun, Chenfeng Wu, Sanatan Sharma, Abhishek Rajkumar Sethi, Deepak Vasisht, and Dinesh Bharadia. 2020. Deep Learning Based Wireless Localization for Indoor Navigation.

[10]

George Boateng, Vivian Genaro Motti, Varun Mishra, John A. Batsis, Josiah Hester, and David Kotz. 2019. Experience: Design, Development and Evaluation of a Wearable Device for MHealth Applications. In The 25th Annual International Conference on Mobile Computing and Networking (MobiCom '19). Article 31, 14 pages.

Digital Library

[11]

Oscar Canovas, Pedro E. Lopez-de Teruel, and Alberto Ruiz. 2017. Detecting Indoor/Outdoor Places Using WiFi Signals and AdaBoost. IEEE Sensors Journal 17, 5 (2017), 1443--1453.

[12]

Xuetao Ding, Runfeng Zhang, Zhen Mao, Ke Xing, Fangxiao Du, Xingyu Liu, Guoxing Wei, Feifan Yin, Renqing He, and Zhizhao Sun. 2020. Delivery Scope: A New Way of Restaurant Retrieval for On-Demand Food Delivery Service. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery Data Mining (KDD '20). 3026--3034.

Digital Library

[13]

Yi Ding, Ling Liu, Yu Yang, Yunhuai Liu, Desheng Zhang, and Tian He. 2021. From Conception to Retirement: a Lifetime Story of a 3-Year-Old Wireless Beacon System in the Wild. In 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21). 859--872.

Digital Library

[14]

Yi Ding, Yu Yang, Wenchao Jiang, Yunhuai Liu, Tian He, and Desheng Zhang. 2021. Nationwide Deployment and Operation of a Virtual Arrival Detection System in the Wild. In SIGCOMM '21: Proceedings of the 2021 Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication (Sigcomm '21).

[15]

Ele.me. 2021. Fengniao delivery. https://fengniao.ele.me/. [Online; accessed 19-Aug-2021].

[16]

Salma Elmalaki, Lucas Wanner, and Mani Srivastava. 2015. CAreDroid: Adaptation Framework for Android Context-Aware Applications. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking (MobiCom '15). 386--399.

Digital Library

[17]

Aghil Esmaeili Kelishomi, AHS Garmabaki, Mahdi Bahaghighat, and Jianmin Dong. 2019. Mobile User Indoor-Outdoor Detection Through Physical Daily Activities. Sensors (Basel) 19 (2019).

[18]

Google. 2021. Profile battery usage with Batterystats and Battery Historian. https://developer.android.com/topic/performance/power/setup-battery-historian. [Online; accessed 19-Nov-2021].

[19]

Alibaba Group. 2021. Fiscal Year 2020 Annual Report. https://doc.irasia.com/listco/hk/alibabagroup/annual/2020/ar2020.pdf. [Online; accessed 19-Aug-2021].

[20]

Sojeong Ha and Seungjin Choi. 2016. Convolutional neural networks for human activity recognition using multiple accelerometer and gyroscope sensors. In 2016 International Joint Conference on Neural Networks (IJCNN). 381--388.

[21]

Hyung-Sin Kim, JeongGil Ko, and Saewoong Bahk. 2017. Smarter Markets for Smarter Life: Applications, Challenges, and Deployment Experiences. IEEE Communications Magazine 55, 5 (2017), 34--41.

Digital Library

[22]

Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, and Rashmi Vinayak. 2021. Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size. In 2021 International Conference on Machine Learning (ICML 2021).

[23]

Charlene Li, Miranda Mirosa, and Phil Bremer. 2020. Review of Online Food Delivery Platforms and their Impacts on Sustainability. Sustainability 12, 14 (2020).

[24]

Mo Li and Yunhao Liu. 2009. Underground Coal Mine Monitoring with Wireless Sensor Networks. ACM Trans. Sen. Netw. 5, 2, Article 10 (April 2009), 29 pages.

Digital Library

[25]

Yuanjie Li, Chunyi Peng, Zhehui Zhang, Zhaowei Tan, Haotian Deng, Jinghao Zhao, Qianru Li, Yunqi Guo, Kai Ling, Boyan Ding, Hewu Li, and Songwu Lu. 2021. Experience: A Five-Year Retrospective of MobileInsight. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking (MobiCom '21). 28--41.

Digital Library

[26]

Yang Liu, Zhenjiang Li, Zhidan Liu, and Kaishun Wu. 2019. Real-Time Arm Skeleton Tracking and Gesture Inference Tolerant to Missing Wearable Sensors. In Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys '19). 287--299.

Digital Library

[27]

Zhongwei Liu, HyunCheol Park, Zili Chen, and Hosik Cho. 2015. An Energy-Efficient and Robust Indoor-Outdoor Detection Method Based on Cell Identity Map. Procedia Computer Science 56 (2015), 189--195.

[28]

Yao Lu, Aakanksha Chowdhery, and Srikanth Kandula. 2016. Optasia: A Relational Platform for Efficient Large-Scale Video Analytics. In Proceedings of the Seventh ACM Symposium on Cloud Computing (SoCC '16). 57--70.

Digital Library

[29]

Xiaomin Ouyang, Zhiyuan Xie, Jiayu Zhou, Jianwei Huang, and Guoliang Xing. 2021. ClusterFL: A Similarity-Aware Federated Learning System for Human Activity Recognition. In Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys '21). 54--66.

Digital Library

[30]

Valentin Radu, Panagiota Katsikouli, Rik Sarkar, and Mahesh K. Marina. 2014. A Semi-Supervised Learning Approach for Robust Indoor-Outdoor Detection with Smartphones. In Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems (SenSys '14). 280--294.

[31]

Illyyne Saffar, Marie Line Alberi Morel, Kamal Deep Singh, and Cesar Viho. 2019. Semi-Supervised Deep Learning-Based Methods for Indoor Outdoor Detection. In ICC 2019 - 2019 IEEE International Conference on Communications (ICC). 1--7.

[32]

Spencer Sevilla, Matthew Johnson, Pat Kosakanchit, Jenny Liang, and Kurtis Heimerl. 2019. Experiences: Design, Implementation, and Deployment of CoLTE, a Community LTE Solution. In The 25th Annual International Conference on Mobile Computing and Networking (MobiCom '19). Article 45, 16 pages.

Digital Library

[33]

Rakmin Sung, Suk-hoon Jung, and Dongsoo Han. 2015. Sound based indoor and outdoor environment detection for seamless positioning handover. ICT Express 1 (2015), 106--109. Issue 3.

[34]

Yanwen Wang, Jiaxing Shen, and Yuanqing Zheng. 2020. Push the Limit of Acoustic Gesture Recognition. In IEEE INFOCOM 2020 - IEEE Conference on Computer Communications. 566--575.

[35]

Huatao Xu, Pengfei Zhou, Rui Tan, Mo Li, and Guobin Shen. 2021. LIMU-BERT: Unleashing the Potential of Unlabeled Data for IMU Sensing Applications. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems (SenSys '21). 220--233.

Digital Library

[36]

Pengfei Zhou, Yuanqing Zheng, and Mo Li. 2012. How Long to Wait? Predicting Bus Arrival Time with Mobile Phone Based Participatory Sensing. In Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services (Low Wood Bay, Lake District, UK) (MobiSys '12). 379--392.

Digital Library

[37]

Pengfei Zhou, Yuanqing Zheng, Zhenjiang Li, Mo Li, and Guobin Shen. 2012. IODetector: A Generic Service for Indoor Outdoor Detection. In Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems (SenSys '12). 113--126.

Digital Library

[38]

Lin Zhu, Wei Yu, Kairong Zhou, Xing Wang, Wenxing Feng, Pengyu Wang, Ning Chen, and Pei Lee. 2020. Order Fulfillment Cycle Time Estimation for On-Demand Food Delivery. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery Data Mining (KDD '20). 2571--2580.

Digital Library

Cited By

Zhu J(2024)A Big Data-Driven Unsupervised Indoor and Outdoor Detection Approach Using Deep Contrastive Learning2024 4th International Conference on Consumer Electronics and Computer Engineering (ICCECE)10.1109/ICCECE61317.2024.10504196(285-288)Online publication date: 12-Jan-2024
https://doi.org/10.1109/ICCECE61317.2024.10504196
Hu YFan XYin ZQian FJi ZShu YHan YXu QLiu JBahl PCosta XAl Hassanieh HAsadi ACox LPerino DWidmer JGiustiniano D(2023)The Wisdom of 1,170 Teams: Lessons and Experiences from a Large Indoor Localization CompetitionProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3592507(1-15)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1145/3570361.3592507
Styła MKiczek BKłosowski GRymarczyk TAdamkiewicz PWójcik DCieplak T(2022)Machine Learning-Enhanced Radio Tomographic Device for Energy Optimization in Smart BuildingsEnergies10.3390/en1601027516:1(275)Online publication date: 27-Dec-2022
https://doi.org/10.3390/en16010275
Show More Cited By

Index Terms

Experience: adopting indoor outdoor detection in on-demand food delivery business

Recommendations

Experience: practical indoor localization for malls
MobiCom '22: Proceedings of the 28th Annual International Conference on Mobile Computing And Networking

We report our experiences of developing, deploying, and evaluating MLoc, a smartphone-based indoor localization system for malls. MLoc uses Bluetooth Low Energy RSSI and geomagnetic field strength as fingerprints. We develop efficient approaches for ...
Experience: pushing indoor localization from laboratory to the wild
MobiCom '22: Proceedings of the 28th Annual International Conference on Mobile Computing And Networking

While GPS-based outdoor localization has become a norm, very few indoor localization systems have been deployed and used. In this paper, we share our 5-year experience on the design, development and evaluation of a large-scale WiFi indoor localization ...
Environmental exposure assessment using indoor/outdoor detection on smartphones

We present an energy-efficient method for Indoor/Outdoor detection on smartphones. The creation of an accurate environmental exposure detection method enables crucial advances to a number of health sciences, which seek to model patients' environmental ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

MobiCom '22: Proceedings of the 28th Annual International Conference on Mobile Computing And Networking

October 2022

932 pages

ISBN:9781450391818

DOI:10.1145/3495243

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 October 2022

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

National Research Foundation Singapore, Pre-positioning (IAF-PP) Funding Initiative, Alibaba Group through Alibaba Innovative Research (AIR) Program and Alibaba-NTU Singapore Joint Research Institute (JRI), and Ministry of Education Singapore MOE AcRF Tier 2 MOE-T2EP20220-0004.

Conference

ACM MobiCom '22

Sponsor:

SIGMOBILE

ACM MobiCom '22: The 28th Annual International Conference on Mobile Computing and Networking

October 17 - 21, 2022

NSW, Sydney, Australia

Acceptance Rates

Overall Acceptance Rate 440 of 2,972 submissions, 15%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
457
Total Downloads

Downloads (Last 12 months)101
Downloads (Last 6 weeks)7

Reflects downloads up to 21 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Zhu J(2024)A Big Data-Driven Unsupervised Indoor and Outdoor Detection Approach Using Deep Contrastive Learning2024 4th International Conference on Consumer Electronics and Computer Engineering (ICCECE)10.1109/ICCECE61317.2024.10504196(285-288)Online publication date: 12-Jan-2024
https://doi.org/10.1109/ICCECE61317.2024.10504196
Hu YFan XYin ZQian FJi ZShu YHan YXu QLiu JBahl PCosta XAl Hassanieh HAsadi ACox LPerino DWidmer JGiustiniano D(2023)The Wisdom of 1,170 Teams: Lessons and Experiences from a Large Indoor Localization CompetitionProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3592507(1-15)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1145/3570361.3592507
Styła MKiczek BKłosowski GRymarczyk TAdamkiewicz PWójcik DCieplak T(2022)Machine Learning-Enhanced Radio Tomographic Device for Energy Optimization in Smart BuildingsEnergies10.3390/en1601027516:1(275)Online publication date: 27-Dec-2022
https://doi.org/10.3390/en16010275
Ni JZhang FXiong JHuang QChang ZMa JXie BWang PBian GLi XLiu C(2022)ExperienceProceedings of the 28th Annual International Conference on Mobile Computing And Networking10.1145/3495243.3560546(147-157)Online publication date: 14-Oct-2022
https://dl.acm.org/doi/10.1145/3495243.3560546

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents