Author: Albert Su, Date: November 19, 2016, Title: Project Vulcan
Project Vulcan is an unmanned aerial vehicle (UAV) open project for discovery and exploration of drone technologies. Drones can be controlled by a human operator located on the ground or can be controlled fully autonomously using GPS guidance. Onboard computers provide flight guidance and stabilization from sensor such as ultrasound that detects ground altitude, gyroscopes that detects axis, accelerometer detects the speed, magnetometers detects magnetic fields, and pressure sensors to detect the altitude, all runs autonomously. The implications of the UAV were initially used in the military where manned missions were too dangerous. Today, UAVs are becoming more popular in recreational applications and in civil applications.
Toscano, M. (2015, May). Drone market in commercial/civilian side will outgrow military by 14% between 2015 and 2020. The industry is growing for commercial/civilian drones by a compound annual rate of 19% between 2015 and 2020. During this time, commercial/civilian drones are extending beyond military applications into industries such as agriculture, energy, utilities, mining, construction, real estate, news media, and film production. The drone market size will reach $82 billion dollars by 2025 employing 100,000 people. From Andrea, R. (2014), IEEE journal, drones are used to speed deliver packages to consumers. Jeff Bezos, CEO of Amazon.com, showcased a plan for these drones to deliver Amazon packages to customers. In Swedberg, C. (2014, September), RFID-Reading Drone Tracks Structural Steel Products in Storage Yard, points out drones tracking inventory can be done with 98% accuracy and much quicker than a human checking inventory in a large area under difficult environmental conditions such as very hot weather. Given drones operate quickly in large areas and under difficult environmental condition, search and rescue drones are being developed to deliver medial care to patients, Hallewas, C. (2014), TU Delft’s ambulance drone drastically increases chances of survival of cardiac arrest patients. In this scnario, a drone was carrying a defibrillator to be quickly delivered to a patient. From Cho, J. (2014), Innovation of Health Check Process Using RFID and Mobile Devices: Samsung Medical Center Case, takes the drone search and rescue application and integrates this into the medical care system. Thereby taking data from the patient to drone to informational technologies (IT). This system utilizes an array of hardware such as sensors, drones, onboard computers, Internet of Things (IOT), smart phones, cloud servers and software such as smart phone applications, cloud applications, and controller firmware applications.
Current research from scholarly journal indicates much of the basic has already been done. For instance, the RFID tag to actively monitor patients from IEEE journal article, Design of a Passively-Powered, Programmable Sensing Platform for UHF RFID Systems, by Sample, A., Yeager, D., Powledge, P., Smith, J. (2007), has applications for monitoring vital signs such as heartbeat. Other applications for implementation are cloud and network applications. For instance, once the drone has received the data from the patient’s wrist sensor, the emergency rescue crew can pull up any critical medical information about the patient via the cloud. Quickly, the emergency rescue crew gains valuable information and time to make better emergency response decisions such as does this patient need an insulin shot, asthma inhaler, or defibrillator? Once a decision is made, a swarm of drones can quickly fly to the patient who is injured and lost on a remote mountainous trail. As rescue teams are dispatched, a swam of drones reach the patient quickly within a 12 kilometer range in about one minute, Hallewas, C. (2014). Once the patient is located, the swam of drones relay video and vital data via a cloud base drone network communicating information back to the emergency operator, Edmondson, J. (2012). From a remote location, the drone operator views the patient from virtual reality Head-Mounted Displays (HMD) seeing what the drones sees, Fan, K., Seigneur, J., Guislain, J., Nanayakkara, S., Inami, M. (2016). In this scenario drone benefit search and rescue operations, can this application be applied to action sports?
HMD is geared for action sports, Augmented Winter Ski with AR HMD, Fan, K., Seigneur, J., Guislain, J., Nanayakkara, S., Inami, M. (2016), and is geared with drones such as the AR Drone by Parrot company, Parrot. (2016). Currently, action sports uses drones for movie making such as triathlons (Ironman, Xterra) where a drone is shown to capture the beginning of the race, SuperFly.tv. (2015). Moreover, drones can be developed to track athletes in a race where a large number of assets (athletes, bikes, equipment) to be monitor over a large area. In this case, wrist sensors, iAutomate.com, (2016), is attached to the athlete and asset tracking a sensor is attached to the bike. The RFID reader on the drone can then track up to a 1000 athletes in 10,000 square meters within five minutes as opposed to conventional RFID systems tracking 300 athletes in eight square meters, RFID, (2016). Furthermore, drones response time is quicker tracking down a lost or injured athlete during a race over challenging terrain over a large area of land and sea would take human emergency crews a great deal of time. In addition to the drone, a smart phone application with an emergency alert function, iSurvive (2016), can send a SMS SOS message notifying first responder of their location and a drone can be programmed to autonomously fly to the athletes location, Parrot, (2016).
The opportunities of this drone system in action sports can also be applied to other functional areas in a number of industries. These functional areas such monitoring, asset/fleet management, cloud asset management, search and rescue, and media are applicable in industries such as agriculture, energy, utilities, mining, construction, real estate, news media, and film production.
The risks of this new technology are multilevel with a resistance to change. In Lapointe, L., Suzanne, R. (2005), A Multilevel Model of Resistance to Information Technology Implementation, gives examples where new informational technology systems implemented failed because the system posed a threat to the people using the system.
Overall, the benefits of drones and opportunities for drones to aid and facilitate business processes in a variety of industries are growing. We focused on how might drones and this system may impact the world of action sports.
- Problem – Identify a large problem affecting the world.
- Solution – Propose a radical solution for solving that problem.
- Technology – Provide a reason with analysis and research methods (quantitative, qualitative, mixed) that these technologies can work.
- Drone Batteries
- AR Glasses for Drones (Epson)
- Passenger Drones (Ehang 184)
- AI Pilotless Autonomous Drones (IEEE)
* Andrea, R. (2014). Guest Editorial: Can Drones Deliver? IEEE Transactions On Automation Science and Engineering, Vol. 11, No. 3. pp. 647-648. Retrieved from http://sfxhosted.exlibrisgroup.com/waldenu?sid=google&auinit=R&aulast=D%27Andrea&atitle=Guest+editorial+can+drones+deliver%3F&id=doi:10.1109/TASE.2014.2326952&title=IEEE+Transactions+on+Automation+Science+and+Engineering&volume=11&issue=3&date=2014&spage=647&issn=1545-5955
* Brunstetter, D., Braun, M. (2011). The Implications of Drones on the Just War Tradition. Retrieved from http://sfxhosted.exlibrisgroup.com/waldenu?sid=google&auinit=D&aulast=Brunstetter&atitle=The+implications+of+drones+on+the+just+war+tradition&id=doi:10.1017/S0892679411000281&title=Ethics+%26+International+Affairs&volume=25&issue=03&date=2011&spage=337&issn=0892-6794
* Edmondson, J. (2012). Approximation Techniques for Maintaining
Real-time Deployments Informed by User-provided
Dataflows Within a Cloud. Retrieved from http://www.computer.org/csdl/proceedings/srds/2012/2397/00/4784a372.pdf
* Fan, K., Seigneur, J., Guislain, J., Nanayakkara, S., Inami, M. (2016). Augmented Winter Ski with AR HMD. Retrieved from http://archive-ouverte.unige.ch/unige:80472
Swedberg, C. (2014, September). RFID-Reading Drone Tracks Structural Steel Products in Storage Yard. Retrieved from http://www.rfidjournal.com/articles/view?12209/
Toscano, M. (2015, May). THE DRONES REPORT: Market forecasts, regulatory barriers, top vendors, and leading commercial applications. Retrieved from http://www.businessinsider.com/uav-or-commercial-drone-market-forecast-2015-2
Sample, A., Yeager, D., Powledge, P., Smith, J. (2007). Design of a Passively-Powered, Programmable Sensing Platform for UHF RFID Systems. Retrieved from https://sensor.cs.washington.edu/pubs/WISP-IEEE-RFID07-PostConf.pdf
Cho, J. (2014). Innovation of Health Check Process Using RFID and Mobile Devices: Samsung Medical Center Case. Retrieved from http://www.wbiworldconpro.com/uploads/new-york-conference-2014/management/1401686160_401-June.pdf
RFID. (2016). RFID Race Timing Systems. Retrieved from http://rfidtiming.com/wp-content/uploads/2016/03/RFID-Ultra-Brochure-A4-Mar16.pdf
iAutomate.com, (2016). Wavetrend RX1510 Long Range GPRS RFID Reader. Retrieved from http://www.iautomate.com/products/wavetrend-rx1510-long-range-gprs-rfid-reader.html
Parrot. (2016). File: ARDone2. Retrieved from http://www.parrot.com/usa/gallery/ardrone2/
Lapointe, L., Suzanne, R. (2005). A Multilevel Model of Resistance to Information Technology Implementation. MIS Quarterly. Vol. 29, No. 3. pp.461-491
SuperFly.tv. (2015). The Ironman Triathlon Drone Shoot. Retrieved from https://vimeo.com/134946065
Hallewas, C. (2014). TU Delft’s ambulance drone drastically increases chances of survival of cardiac arrest patients. Retrieved from http://www.tudelft.nl/en/current/latest-news/article/detail/ambulance-drone-tu-delft-vergroot-overlevingskans-bij-hartstilstand-drastisch/
iSurvive. (2016). Features. Retrieved from http://www.isurviverescueapp.com/features#