Rajalakshmi Nandakumar

Dhwani: secure peer-to-peer acoustic NFC

Near Field Communication (NFC) enables physically proximate devices to communicate over very short ranges in a peer-to-peer manner without incurring complex network configuration overheads. However, adoption of NFC-enabled applications has been stymied by the low levels of penetration of NFC hardware. In this paper, we address the challenge of enabling NFC-like capability on the existing base of mobile phones. To this end, we develop Dhwani, a novel, acoustics-based NFC system that uses the microphone and speakers on mobile phones, thus eliminating the need for any specialized NFC hardware. A key feature of Dhwani is the JamSecure technique, which uses self-jamming coupled with self-interference cancellation at the receiver, to provide an information-theoretically secure communication channel between the devices. Our current implementation of Dhwani achieves data rates of up to 2.4 Kbps, which is sufficient for most existing NFC applications.

FingerIO: Using Active Sonar for Fine-Grained Finger Tracking

We present fingerIO, a novel fine-grained finger tracking solution for around-device interaction. FingerIO does not require instrumenting the finger with sensors and works even in the presence of occlusions between the finger and the device. We achieve this by transforming the device into an active sonar system that transmits inaudible sound signals and tracks the echoes of the finger at its microphones. To achieve sub-centimeter level tracking accuracies, we present an innovative approach that use a modulation technique commonly used in wireless communication called Orthogonal Frequency Division Multiplexing (OFDM). Our evaluation shows that fingerIO can achieve 2-D finger tracking with an average accuracy of 8 mm using the in-built microphones and speaker of a Samsung Galaxy S4. It also tracks subtle finger motion around the device, even when the phone is in the pocket. Finally, we prototype a smart watch form-factor fingerIO device and show that it can extend the interaction space to a 0.5×0.25 m2 region on either side of the device and work even when it is fully occluded from the finger.

Feasibility and limits of wi-fi imaging

We explore the feasibility of achieving computational imaging using Wi-Fi signals. To achieve this, we leverage multi-path propagation that results in wireless signals bouncing off of objects before arriving at the receiver. These reflections effectively light up the objects, which we use to perform imaging. Our algorithms separate the multi-path reflections from different objects into an image. They can also extract depth information where objects in the same direction, but at different distances to the receiver, can be identified. We implement a prototype wireless receiver using USRP-N210s at 2.4 GHz and demonstrate that it can image objects such as leather couches and metallic shapes in line-of-sight and non-line-of-sight scenarios. We also demonstrate proof-of-concept applications including localization of static humans and objects, without the need for tagging them with RF devices. Our results show that we can localize static human subjects and metallic objects with a median accuracy of 26 and 15 cm respectively. Finally, we discuss the limits of our Wi-Fi based approach to imaging.

GlimpseData: towards continuous vision-based personal analytics

Emerging wearable devices provide a new opportunity for mobile context-aware applications to use continuous audio/video sensing data as primitive inputs. Due to the high-datarate and compute-intensive nature of the inputs, it is important to design frameworks and applications to be efficient. We present the GlimpseData framework to collect and analyze data for studying continuous high-datarate mobile perception. As a case study, we show that we can use low-powered sensors as a filter to avoid sensing and processing video for face detection. Our relatively simple mechanism avoids processing roughly 60% of video frames while missing only 10% of frames with faces in them.

CovertBand: Activity Information Leakage using Music

This paper contributes a novel method for low-cost, covert physical sensing and, by doing so, surfaces new privacy threats. We demonstrate how a smartphone and portable speaker playing music with embedded, inaudible signals can track multiple individuals’ locations and activities both within a room and through barriers in 2D space. We achieve this by transforming a smartphone into an active sonar system that emits a combination of a sonar pulse and music and listens to the reflections off of humans in the environment. Our implementation, CovertBand, monitors minute changes to these reflections to track multiple people concurrently and to recognize different types of motion, leaking information about where people are in addition to what they may be doing. We evaluated CovertBand by running experiments in five homes in the Seattle area, showing that we can localize both single and multiple individuals through barriers. These tests show CovertBand can track walking subjects with a mean tracking error of 18 cm and subjects moving at a fixed position with an accuracy of 8 cm at up to 6 m in line-of-sight and 3 m through barriers. We test a variety of rhythmic motions such as pumping arms, jumping, and supine pelvic tilts in through-wall scenarios and show that they produce discernibly different spectrograms from walking in the acoustic reflections. In tests with 33 subjects, we also show that even in ideal scenarios, listeners were unlikely to detect a CovertBand attack.

Charging a Smartphone Across a Room Using Lasers

We demonstrate a novel laser-based wireless power delivery system that can charge mobile devices such as smartphones across a room. The key challenges in achieving this are multi-fold: delivering greater than a watt of power across the room, minimizing the exposure of the resulting high-power lasers to human tissue, and finally ensuring that the design meets the form-factor requirements of a smartphone and requires minimal instrumentation to the environment. This paper presents a novel, and to the best of our knowledge, the first design, implementation and evaluation of an end-to-end power delivery system that satisfies all the above requirements. Our results show that we can deliver more than 2 W at ranges of 4.3 m and 12.2 m for a smartphone (25 cm2) and table-top form factor (100 cm2) receiver respectively. Further, extensive characterization of our safety system shows that we can turn off our laser source much before a human moving at a maximum speed of 44 m/s can even enter the high-power laser beam area.

3D Localization for Sub-Centimeter Sized Devices

The vision of tracking small IoT devices runs into the reality of localization technologies --- today it is difficult to continuously track objects through walls in homes and warehouses on a coin cell battery. While Wi-Fi and ultra-wideband radios can provide tracking through walls, they do not last more than a month on small coin and button cell batteries since they consume tens of milliwatts of power. We present the first localization system that consumes microwatts of power at a mobile device and can be localized across multiple rooms in settings like homes and hospitals. To this end, we introduce a multi-band backscatter prototype that operates across 900 MHz, 2.4 and 5 GHz and can extract the backscatter phase information from signals that are below the noise floor. We build sub-centimeter sized prototypes which consume 93 μW and could last five to ten years on button cell batteries. We achieved ranges of up to 60 m away from the AP and accuracies of 2, 12, 50 and 145 cm at 1, 5, 30 and 60 m respectively. To demonstrate the potential of our design, we deploy it in two real-world scenarios: five homes in a metropolitan area and the surgery wing of a hospital in patient pre-op and post-op rooms as well as storage facilities.

Unleashing the Power of Active Sonar

The authors explore various applications that can be enabled by transforming mobile devices into active sonar systems. Specifically, they show how to use microphones and speakers available on existing smartphones to monitor minute body movements such as breathing. Using this, they build systems that will demonstrate the feasibility of achieving contactless solutions for sleep apnea diagnosis. Building on their active sonar approach, they also demonstrate the feasibility of subcentimeter finger tracking for around-device interaction using existing smartphones with no additional hardware. The resulting finger tracking system breaks a fundamental tension between the shrinking sizes of wearable and mobile devices and our ability to interact with them and achieves this without the need for additional hardware.