People of ACM - Moustafa Youssef
December 3, 2020
What led to your interest in mobile networks, and, more specifically, location tracking algorithms?
When I was starting to work on my PhD, WiFi networks were just beginning to gain momentum. Mobile phones at that time were not smart. Early on, I thought about the possibility of leveraging WiFi signals to provide indoor localization as a value-added service to WiFi networks. This led to the design and implementation of the Horus WiFi-based location determination system, one of the earliest and most cited works in the field. Horus stands as a game changer in this domain. It identified and overcame the key challenges that hindered real deployments of WiFi-based localization systems early on. Specifically, it identified the different causes of localization error and how they relate to the properties of wireless signal propagation, correlation between RSS samples, and energy efficiency—all key to enabling commercial deployment of WiFi-based localization systems. Horus’s early contributions opened the door to a large number of followup papers that model WiFi-localization system performance, obtain error bounds, and experiment with different solutions for handling causes of error. Horus also won the 2003 Invention of the Year Award from the University of Maryland.
Considering that indoor localization is a hard problem, with no equivalent ubiquitous indoor tracking system like GPS indoors, my group continued addressing more challenges in this exciting domain. For example, our CrowdInside system addresses one of the major showstoppers for ubiquitous indoor localization, namely the unavailability of indoor floor plans on a worldwide scale. CrowdInside introduced the idea of leveraging standard smartphone sensors in a crowdsourced manner to automatically construct indoor floor plans by a building’s everyday users. This not only provided a solution to one of the hurdles of ubiquitous indoor localization, but it also sparked follow-on work that builds different layers of semantics on top of the estimated floor plans such as points of interest and place functionalities.
What was a key insight you, along with your co-author Heba Aly, introduced in Dejavu: an accurate energy-efficient outdoor localization system, for which you received the 2013 ACM SIGSPATIAL GIS Best Paper Award?
GPS is a ubiquitous outdoor localization system that can provide user location outdoors almost anywhere around the world. However, there are situations where GPS does not work, e.g. in urban canyons, and it can drain the mobile device battery quickly. Our Dejavu system provides an energy-efficient, highly accurate outdoor GPS-replacement technology. Before Dejavu, GPS-replacement systems usually traded accuracy for energy efficiency. Dejavu uses energy-efficient smartphone sensors to detect virtual landmarks in the physical space that can be used for accurate pinpointing of the user location and resetting the accumulated error from dead-reckoning. Our results show that Dejavu can obtain better accuracy than GPS in in-city driving conditions, while leading to an order of magnitude savings in energy consumption. Dejavu also won the 2015 COMESA Innovation Award.
Can you share with us how you and your colleagues came up with the idea of device-free sensing and its impact on the location-tracking field?
When we were working on WiFi localization, changes in the received signal were considered a source of noise that led to a reduction in localization accuracy. Our team thought about leveraging the changes in the received signal as a source of information, rather than noise. This was the birth of the device-free localization concept that we introduced in our 2007 ACM SIGMOBILE Vision/Challenges paper. The main idea is to leverage changes in the ambient RF signals to track entities, detect what they are doing, and sense the environment, without attaching any devices to them. This is in comparison to traditional tracking and sensing techniques, such as GPS and traditional sensor networks, that require a specific device to be attached to the tracked entity. This paradigm-shifting approach for localization and sensing opened the door for an array of novel applications such as intrusion detection, smart homes, sensorless sensing, through-the-wall sensing, activity recognition, and ubiquitous gesture-controlled IoT devices, among many others. It is now considered one of the hot topics in location tracking and sensing research.
What is an exciting new frontier in location tracking, or mobile systems more broadly?
With the booming of the Internet of Things and their expected wide deployment, we thought about how we can extend the concept of device-free sensing to the IoT to meet their challenges. Specifically, many of the IoT devices are expected to be limited in capability and run with minimal power sources/limited battery. To extend their lifetime, autonomy, and reduce the cost of deployment, we introduced the concept of energy-free sensing in our IEEE Pervasive Computing magazine vision paper (published December 2019) and showed a proof-of-concept system for this vision in an ACM MobiCom paper. The goal of energy-free sensing is to sense the environment while consuming minimal or no energy. We envision a future where many IoT devices will be self-powered with energy harvesting hardware such as RF or solar energy harvesting. Or idea is to leverage the changes in the harvested energy to sense what is going on in the environment. For example, a user doing a gesture with an IoT device powered by a solar panel will interrupt the light incident to the panel in a specific pattern that is correlated with the performed gesture. By analyzing the changes in the harvested current, one would be able to detect the performed gesture. Since we are leveraging the harvested energy as a source of information, we could virtually consume zero extra power to sense the environment.
Another interesting frontier in location tracking is determining the user indoor location in 3D. Traditionally, research in the area focused on 2D localization. However, there are many scenarios where 3D localization can provide not only commercial value, but also save lives. These include indoor navigation, directed ads, indoor analytics, and indoor emergency services (E911). Of particular interest in this domain is localization using cellular signals, since it is available on all mobile devices, and can provide truly ubiquitous 3D indoor localization, an environment where GPS does not work. A number of challenges need to be addressed, including the noisy wireless propagation, the large range of a cellular tower, and reducing the deployment overhead.
How do academia and industry in Egypt promote the field of mobile computing?
Things are changing rapidly in this interesting field. Many startups are trying to leverage mobile devices to provide new services. Mobile computing lies at the heart of these services and concepts like device-free and energy-free sensing provide a value-added revenue stream. Attracting top students to work on this exciting field builds on acquiring funds from top companies, not only in Egypt, but worldwide. Several of our students have won awards such as graduate and undergraduate student research competitions from different ACM Special Interest Groups. Other achievements include winning the competitive Google Fellowship, COMESA Innovation Award, and Best Paper awards. We are proud of our students and hopeful about the bright future of the mobile computing field in Egypt and the region.
Moustafa Youssef is a Professor and Director of the Wireless Research Center at Alexandria University and the American University in Cairo (Egypt). His research interests include mobile wireless networks, mobile computing, location determination technologies, and pervasive computing. Youssef has more than 20 issued and pending patents on technologies related to mobile systems.
His honors include receiving the 2013 ACM SIGSPATIAL GIS Best Paper Award, a 2017 Egyptian State Excellence Award, and numerous Google Research Awards, among many others. Youssef is an Associate Editor for ACM Transactions on Spatial Algorithms and Systems (TSAS). He was named an ACM Fellow in 2019 for contributions to location tracking algorithms.