Building Energy Optimization

ePrints: Personal Energy Footprinting

With the rise of population and emergence of Smart Buildings and Smart Cities, conserving energy is of prime importance. While people are careful about their usage at home, energy wastage in public buildings/offices goes unaccounted for as users do not pay for it. We develop a system that can generate real-time energy footprint for all users and provide related data analytics to help conserve their energy and even implement advanced functionalities such as prediction and  modeling.

[Project Page] [BuildSys 2017] [TOSN 2018]

RecEnergy: An Energy Saving Recommender System

Example Energy Saving Recommendation, with energy metrics.

Recent research efforts have made significant progress in reducing commercial building energy consumption through a variety of methods, including optimizing building heating, ventilation, and air conditioning (HVAC), lighting, and personal electric devices. However, these works focus on reducing energy consuming resources while treating occupants as immovable objects separate from the building energy optimization problem.

RecEnergy is a recommender system for reducing energy consumption in commercial buildings with human-in-the-loop. We formulate the building energy optimization problem as a Markov Decision Process, show how deep reinforcement learning can be used to learn energy saving recommendations, and effectively engage occupants in energy-saving actions.

[Project Page] [UMAP 2018] [IOTJ 2020]

CityEnergy: City-Scale Energy Footprinting

Example energy and population estimates for different buildings at 8 am in Manhattan.

In urban cities such as New York City, buildings are responsible for up to 75% of total greenhouse gas emissions, and over 90% of total benchmarked energy consumption. A significant portion of the energy consumed directly services humans in retail, commercial, and residential buildings. As sustainability increasingly becomes an important factor in modern society, energy consumption in the built environment is one area where reduction can have a major impact.

CityEnergy is a scalable, real-time system for computing personal energy footprint estimates. As shown in the figure, CityEnergy estimates the energy consumption and population for each building in real-time; these estimates are used to calculate the per capita energy footprint at the building level. CityEnergy is able to provide personal energy footprints to people who provide their location data through a mobile application.

[Project Page] [BuildSys 2019]

PAWS Pedestrian and Biker Safety

Pedestrian SafetyPAWS (formally SEUS) is a smart system that alerts pedestrians and bikers of any possible vehicle collision. Addressing multiple areas of study, PAWS uses sensor fusion and advanced recognition algorithms to locate incoming cars and effectively warns the user to prevent accidents, especially in urban environments.


[Project Page] [Video] [Demo] [Paper][Github]


SPINDLES A Smartphone Platform for Intelligent Detection and Notification of Leg Shaking

For many people, the habit of leg shaking is an annoyance to themselves and people around them. By simply becoming aware of the motion, one is able to voluntarily stop shaking. SPINDLES is a low-power, low-latency, non-intrusive and high accuracy mobile application to detect leg shaking and notify the user in a timely manner. SPINDLES is robust to the placement of the phone and implements a signal processing pipeline that eliminates the need for training and calibration phases common in machine learning approaches.


[Project Page] [Video] [Demo] [Paper]

SPIDERS: Wearable Emotion Sensing

We present a System for Processing In-situ Bio-signal Data for Emotion Recognition and Sensing (SPIDERS)– a low-cost, wireless, glasses-based platform for continuous in-situ monitoring of user’s facial expressions (apparent emotions) and real emotions. We present algorithms to provide four core functions, using the bio-signals acquired from three non-contact sensors. We prototype advanced functionalities including facial expression detection and real emotion classification with a facial expression detector based on landmarks and optical flow that leverages changes in a user’s eyebrows and eye shapes to achieve up to 83.87% accuracy, as well as a pupillometry-based real emotion classifier with higher accuracy than other low-cost wearable platforms that use sensors requiring skin contact. SPIDERS costs less than $20 to assemble and can continuously run for up to 9 hours before recharging.

[Project Page] [Video] [Demo] [Paper]

Zika Virus Monitoring

Zika Virus

The goal is to identify and map possible breeding grounds of Zika carrying mosquitoes.

  • Using geotagged images, temperature, humidity and wind velocity information with a drone and perhaps some form of readily available datasets.
  • Involves quality assessment of images to reject images with blurs and distortions.
  • Figure out breeding grounds hotspots by distinguishing images showing tires, stagnant water, etc. along with integrating with data from temperature, humidity and wind sensors.
  • Visualize a heat map based on the probability of a location being a potential breeding ground of Zika carrying mosquitoes.
  • Make such heatmaps/visualizations available to concerned health/government authorities for them to take suitable preventive measures to stop the spread of the disease.
  • Potentially identify the data correlation between ambient conditions & the Zika Virus.

[Project Page] [Video] [Demo] [Paper]


Intelligent and Privacy-Preserving Pillbox


We present a novel privacy-preserving pillbox system to help patients improve medication adherence while maintaining privacy and security. Existing smart pillbox systems have been successful in notifying, tracking and reporting medication adherence, but do not provide sufficient security and privacy for the patients’ medication adherence records. In the proposed system, we protect data that needs to be reported to the doctor by ensuring that the data can only be decrypted by the doctor, authorized by a face-to-face key exchange process through out-of-band communication channels. Our system also gives patients fine-grained control over how their information is transmitted and shared, which has been a major privacy concern for many patients.

[Project Page] [Video] [Demo] [Paper]



RIO 40C Smart Sunburn Monitor


RIS – a smart wearable device that can prevent sunburns

  • Low Cost
  • Wearable
  • Wireless
  • Multi sensor
  • Smartphone compatible
  • Personal UV indicator

[Project Page] [Video] [Demo] [Paper]


Textile-based Perspiration Sensing

We present a novel wearable sensor system that measures an individual’s sweat level. The system consists of multiple cotton-covered conductive threads that are then braided into one sensor. The braided 3D structure allows robust perspiration level estimation despite the sensor distortion or the motion of the person.


[Project Page] [Video] [Demo] [Paper]