Package Delivery System Using GPS Drones

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Package Delivery System Using GPS Drones

Aditya Bhardwaj

B. Tech CSE 3rd Year SRM IST

Achira Basu

  1. Tech CSE 3rd Year SRM IST

    Dr. A.Senthil Selvi Associate Professor SRM IST

    Abstract – Drone Delivery system will track live location of consumer and hence provide assured delivery of package to the correct place and correct person. GPS Drone delivery system will locate the consumer through GPS and detect the live location and deliver the package accurately and within a stipulated time as per the date of delivery.GPS will be inbuilt in the drone and live tracking device will detect the location of users device which will currently be handled by the customer using OTP provided during generation of package to avoid fraud. There will be a main warehouse and some sub-warehouses, the drone will pick up the package from the nearest warehouse of the delivery location. It will behave like any home delivery app where both the customer and the dispatcher will be able to trace the live location of the package.

    Keywords – Drone, GPS, OTP


      Courier delivery system in the recent time is still not 100% efficient. Several times it does not reach the consumer because of incorrect delivery details or wrong address detection. Sometimes it reaches late, that is after its requirement day and the other times it does not reach. After it returns, customers have to go and collect it themselves. GPS Drone delivery system will locate the consumer through GPS of the tracking device and detect the live location to deliver the package accurately within a stipulated time as per scheduled delivery. It will ensure that the package reaches the customer and he does not have to hassle for collecting the package.

    2. DRONES

      Figure 1 shows the pictorial view of Multi-rotor drones. These kinds of drones have strong robotic arms and more pickup capacity than other kinds of drones. These can be used for longer range delivery and heavy package delivery. The arms will extend and carry the package. The control ensures that the load is properly attached and the right route is followed. These can carry the load over longer distances.

      Figure 1: Multi-rotor drones

      Figure 2: Quadcopter Drones

      Figure 3: Fixed Wing Drones

      Figure 2 shows the pictorial view of Quadcopter Drones. These drones have little less carrying capacity than heavy weight carrying drones. None the less, it can also fly over great distances to deliver the package. the body is lighter and can fly up to greater altitude to avoid disturbances and obstacles. Extra arms can be modified into these types of drones.

      Figure 3 shows the pictorial view of Fixed Wing Drones. These drones can cover a stipulated distance with immense speed and in a very short time. The delivery time is short and fast. It can deliver intracity. The only drawback is that the package has to be lightweight and it cannot carry much weight.

    3. ORGAN USED IN TRACKING SYSTEM The important organ used in tracking system are-

      • GSM Provider

      • Vehicle or person with suitable device

      • Location tracking server

      • GPS Satellite

      • Client System

      The GPS satellite sends the radio signal to the device which temporarily stores our data in their system, the device is stored in both the vehicle we drive as well as GPS compatible device we carry with us that is phone. The device is also provided with the panic button in case of emergency tracking. The tracking devices are consist of a SIM Card which is used to communicate with the nearest GSM network and thus the tracking system works with the help of both GSM networks and GPS. The tracking server has software to catch the signal sent by the device which is being tracked. The received data are in the hexadecimal format and are further converted into the readable format with the help of parser and converter, then the data are stored in the database and processed to further actions.



        Figure 4 shows flowchart of Working Module of Drones. The base or the warehouse receives signal for the dispatch of the package. The base then transfers the signal to the allotted drone. It flies out rising to a higher altitude to avoid obstacles and disturbances. The path is set to the delivery location and the drone tarts towards its destination. After it flies to the higher altitude, the drone is provided with the immediate location of the customer and it is constantly updated that is it tracks the location as it moves towards its destination.According to the architecture diagram, the GPS position of the distribution point will be read by the drone. After reading the exact position it will continuously monitor the current location and take it away from the base. It will fly to the delivery point and confirm the package to the correct customer by asking for the OTP sent to the verified device. After confirmation it will deliver the package and take it back from the delivery point to the base. In case the OTP is not valid that is, it does not verify, the drone will not lower itself and fly back to the base. The process will repeat itself until the package is reached to its customer.

        Figure 4: Flowchart of Working Module of Drones


        Figure 5 shows the working of dron base. This is an abstract of a drone base created in a particular area that will operate in a specific zone. In case the delivery location is out of its boundary it will communicate with nearest bases. Then it delivers the package to the nearest base to the delivery location. Figure 6 shows how the base communicates with the customer and sends a drone with the required package on its path to deliver it to the customer. The drone will deliver the package to the customer only if it is 100 meters within the delivery location (the location provided at the time of order).

        Figure 5: Drone Base

        Figure 6: Base interaction with Customer


        Figure 7 show the user system interaction Long distance vehicles carrying more payloads require more energy and batteries for each unit of travel. Larger multi-stop vehicles carry more battery and payload and pay for it in drag. Vehicles are conservatively sized to be able to traverse the entire delivery route and return to the fulfillment center with all packages. The burden of irreversible packages increases with each additional package and with compounds. On the delivery date the information is sent to the customers phone and he updates the system with either his live location. If the payment is received on delivery the drone collects the payment in a safe-box installed in the central controlling head. The drone reached the users location but before lowering itself , the OTP is confirmed. The drone has to be provided with a unique feature so that there is no interchange with some other customers packages to ensure that the customer will be provided with a code during the creation of the package on its designated route. As soon as the package reaches the customer, the code will be asked and matched to the number given in the drone. In this way delivery of the correct package will be assured.

        Figure 7: User System Interaction

        Figure 8: Extraction of users location flowchart

        Figure8 shows the process of getting the customers location. While ordering the customer will be asked to provide their address. They will have the option to provide their live location or enter their location manually. In both cases they have to set their location onthe map provided. The drone will have unique design and it will remove obstacles that use image processing to detect any obstacles and be safe during storms and inclement weather. It will reach the people and once reached the location it can be lowered by hand gestures.


        Figure9 shows the location tracking. The location tracking is an important part of this project to ensure the confirm and correct delivery of the package to the customer. The location tracking of the customer will work in two parts. First the customer will provide their location at the time of ordering the product. Then package will be transferred to the nearest main warehouse of that city, and then it will be further transferred to

        the nearest sub warehouse of the locality. The drones will then take the package from the nearest warehouse and fly to the location of the customer provided at the time of ordering the product. The drones will track the customers location through his phone and he should be present within the 100 meters of the provided location, only then the package will delivered otherwise it drone will itself cancel the delivery and fly back to the warehouse from where it picked up the package.

        Figure 9: Location Tracking Flowchart


        Efficiency of proposed method over other methods of package delivery:

        • It is fast and reliable

        • It has the features on in hand delivery

        • It will avoid thefts and hassel faced by customer

        • Customer will not have to wait in a fixed location to collect the parcel

        • It is robust and spontaneous

        • Very efficient over short distances

        • Can be controlled with gestures if modified.

        • Self updating of user location.

      6. ROUTE

      Figure 10 shows the drone route .In drone delivery system, the drones will not be travelling on the present features of the map because they only provide navigation through the road but drones requires a different route that is it have to fly over buildings and reach location as fast as they can. The drones will be provided with different route just like flights. Flights have their own route to travel from one city to another. The drones will be provided with same route as flight but on small scale that is within the city. They will fly over buildings and cover the shortest distance to reach their customer.

      Figure 10: Drone Route

      Figure11 shows the working of drones while selecting the best route to deliver the package to the customer. The drones will be programmed to automatically select the best to reach the customer quickly. The navigation symbol shows the destination and the red shaded area shows the drone base. The navigation on the users end is followed by the map provided by the delivery system to track its drone just like any other tracking system except that the route is by air at not on ground. Anyhow, the drones algorithm detects obstacles and controls its own path and sets accordingly to reach the user, which the user can also see.

      Figure 11: Flowchart of selection of best route by drones


The aspect of this journal is the future of technology. The manual delivery will not be able to satisfy the demands of human race in the future. Drones will become a necessity and will be of immense use in delivery of packages and couriers to the respective customers. In future, people will become so engrossed in their own work that they would not have time for collecting parcels and packages separately. Thus these drones will ensure the correct delivery of their demands in their current positions that is wherever they are. For this system to work properly image processing also has to be implemented in order to remove obstacles in the delivery path. If the dangers or obstacles are intermittent and sudden due to a storm or a bad weather which is harmful, the drones will eliminate it from the path using laser. For a more advanced and efficient system of work and delivery the drone delivery system in the future will be AI controlled that is self processing and implementing. They will be self processing the path if there are any living object as an obstacle through algorithms.


  1. The references and help was taken from the following journals and papers for assistance through some concepts and integration.s

  2. Amazons Drone Patents-Arthur Holland Michel September 2017. (references)‌

  3. What drones can do and how they can do it – Konstantin Kkaes 2012

  4. Recent Developments in Aerial Robotics:

  5. Chun Fui Liew, Danielle DeLatte, Naoya Takeishi, Takehisa Yairi—- 2017

  6. Tracking System using GPS and GSM 2012may Sameer Darekar, Atul Chikane, Rutujit Diwate,‌

  7. Amol Deshmukh, Prof. Archana Shinde

  8. GPS-based Location Tracking System via Android Device nov-13 -Md Nadim

  9. Descartes Route Planner–The Descartes Systems Group Inc. –2011‌

  10. Delivery Planning & Fullment Optimization–Anantpal Singh–2014

  11. Design perspective on delivery dronesJian Xu–2017

  12. SMS-based One-Time Passwords: Collin Mulline, Ravishankar Borgaonkar, Patrick Stewin

  13. A Unique One-Time Password Table Sequence Pattern Authentication –

    B. Balilo Jr. may 17

  14. Senthilselvi.A & Sukumar. R, Removal of salt and pepper noise from images using Hybrid Filter (HF) and Fuzzy Logic Noise Detector (FLND), Concurrency and Computation: Practice and Experience, Volume 31 No 12 June 2019,

  15. Senthilselvi.A,Pradeepmohankumar.K,Dhanasekar.S,UmaMaheswari.P, Ramesh.S,Senthil Pandi.S Denoising of images from salt and pepper noise using hybrid filter,fuzzy logic noise detector and genetic optimization algorithm (HFGOA),Multimedia Tools and Applications, Volume 78 No 14 July 2019, 9.

  16. Mohammed Thaha .M, Pradeep mohan kumar .K Murugan .B.S, Dhanasekar.S,Vijay Karthick .P,Senthilselvi.A Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images, Journal of Medical Systems, Volume 43 No 9 July 2019,

  17. Senthilselvi.A(in press) & Sukumar. R Hybrid Fuzzy Logic and Gravitational Search Algorithm based multiple filters for Image Restoration, International journal of data analysis Techniques and strategies.

  18. For working of Gps Devices and Network


  19. For information regarding Automotive Navigation System‌

  20. For GPSylon System

  21. For Open GTS

  22. FM4xxx Protocols and User Guides. For the study of protocols for the devices used for tracking

  23. What is KML? Why is it used for? How it is used?‌


  25. What is Geofence?

  26. For GPS tracking

  27. unications/11/How_GPS_Tracking_Can_Be_Used‌

  28. Vehicle Tracking

  29. Integration of GPS and GSM for Determination of cellular coverage areaby A. D. Sarma, P. S. Ravikanth and D. Krishna Reddy

  30. Multi-Tracking System using GPS and GSM by Sameer Darekar, Atul Chikane, Prof. Archana Shinde from Proceedings of Interna-tional Conference on ACCT-2012.‌

  31. V. Kumar ad N. Michael, Opportunities and challenges with autonomous micro aerial vehicles, The International Journal of Robotics Research (IJRR), vol. 31, no. 11, pp. 12791291, September 2012.

  32. R. J. Wood, B. Finio, M. Karpelson, K. Ma, N. O. P´erez-Arancibia, P.

    S. Sreetharan, H. Tanaka, and J. P. Whitney, Progress on pico air vehicles, The International Journal of Robotics Research (IJRR), vol. 31, no. 11, pp. 12921302, September 2012.

  33. A. Ollero and K. Kondak, 10 years in the cooperation of unmanned aerial systems, in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2012, pp. 54505451.

  34. D. Mellinger, N. Michael, M. Shomin, and V. Kumar, Recent advances in quadrotor capabilities, in Proc. IEEE International Conference on Robotics and Automation (ICRA), May 2011, pp. 29642965.

  35. S. Lupashin, A. Sch¨ollig, M. Hehn, and R. DAndrea, The flying machine arena as of 2010, in Proc. IEEE International Conference on Robotics and Automation (ICRA), May 2011, pp. 29702971.‌

  36. H. Lim, J. Park, D. Lee, and H. J. Kim, Build your own quadrotor: Open-source projects on unmanned aerial vehicles, IEEE Robotics & Automation Magazine, vol. 19, no. 3, pp. 3345, September 2012.

  37. O. Liang. (2014) Choose flight controller for quadcopter. [Online]. Available: best-flight-controller-quad-hex- copter/‌

  38. O. Liang. (2015) Complete mini quad parts list – FPV quadcopter component choice. [Online]. Available: quad-part-list-fpv/#fc

  39. S. Latscha, M. Kofron, A. Stroffolino, L. Davis, G. Merritt, M. Piccoli, and M. Yim, Design of a hybrid exploration robot for air and land deployment (H.E.R.A.L.D) for urban search and rescue applications, in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2014, pp. 18681873.

  40. J. Butzke, A. Dornbush, and M. Likhachev, 3-d exploration with an air-ground robotic system, in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2015, pp.3241 3248.

  41. B. Das, M. S. Couceiro, and P. A. Vargas, MRoCS: A new multi-robot communication system based on passive action recognition, Robotics and Autonomous Systems (RAS), vol. 82, pp. 4660, August 2016.‌

  42. TagSpaces – Your Hackable File Organizer. [Online].


  43. S. Grzonka, G. Grisetti, and W. Burgard, A fully autonomous indoor quadrotor, IEEE Transactions on Robotics (T-RO), vol. 28, no. 1, pp. 90100, February 2012.‌

  44. K. Kawasaki, M. Zhao, K. Okada, and M. Inaba, MUWA: Multifield universal wheel for air-land vehicle with quad variable-pitch propellers, in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2013, pp. 18801885.

  45. S. Bouabdallah, R. Siegwart, and G. Caprari, Design and control of an indoor coaxial helicopter, in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2006, pp. 2930 2935.

  46. R. Bapst, R. Ritz, L. Meier, and M. Pollefeys, Design and implementation of an unmanned tail-sitter, in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2015,pp. 18851890.

  47. M. Burri, L. Gasser, M. K¨ach, M. Krebs, S. Laube, A. Ledergerber, D. Meier, R. Michaud, L. Mosimann, L. M¨uri, C. Ruch, A. Schaffner, N. Vuilliomenet, J. Weichart, K. Rudin, S. Leutenegger, J. Alonso- Mora,

    R. Siegwart, and P. Beardsley, Design and control of a spherical omnidirectional blimp, in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2013, pp. 1873 1879.

  48. D. Mellinger, N. Michael, and V. Kumar, Trajectory generation and control for precise aggressive maneuvers with quadrotors, The International Journal of Robotics Research (IJRR), vol. 31, no. 5, pp. 664674, April 2012.

Aditya Bhardwaj is a student of SRM Institute of Science and Technology, Chennai, India. He is pursuing his B.Tech degree in Computer Science and Engineering.

Achira Basu is a student of SRM Institute of Science and Technology, Chennai, India. She is pursuing her B.Tech degree in Computer Science and Engineering.

Dr.A. Senthil Selvi is an Associate Professor in the Department of CSE at SRM Institute of Science and Technology, Chennai, India. She received her B.E degree in Electronics and Communication Engineering from Anna University, Tamilnadu, India, in

2005. She has received her M.Tech degree in Information Technology from Kalasalingam University, Tamilnadu, India, in 2010. She has completed her PhD degree in 2019 at Anna University, India

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