Publications
COVID-19 exposure notification in simulated real-world environments
April 15, 2022
Project Report
Published in:
MIT Lincoln Laboratory Report ACTA-3
Summary
Privacy-preserving contact tracing mobile applications, such as those that use the Google-Apple Exposure Notification (GAEN) service, have the potential to limit the spread of COVID-19 in communities, but the privacy-preserving aspects of the protocol make it difficult to assess the performance of the apps in real-world populations. To address this gap, we exercised the CovidWatch app on both Android and iOS phones in a variety of scripted realworld scenarios, relevant to the lives of university students and employees. We collected exposure data from the app and from the lower-level Android service, and compared it to the phones' actual distances and durations of exposure, to assess the sensitivity and specificity of the GAEN service configuration as of February 2021. Based on the app's reported ExposureWindows and alerting thresholds for Low and High alerts, our assessment is that the chosen configuration is highly sensitive under a range of realistic scenarios and conditions. With this configuration, the app is likely to capture many long-duration encounters, even at distances greater than six feet, which may be desirable under conditions with increased risk of airborne transmission.
Summary
Privacy-preserving contact tracing mobile applications, such as those that use the Google-Apple Exposure Notification (GAEN) service, have the potential to limit the spread of COVID-19 in communities, but the privacy-preserving aspects of the protocol make it difficult to assess the performance of the apps in real-world populations. To address this...
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The Simulation of Automated Exposure Notification (SimAEN) Model
April 15, 2022
Project Report
Published in:
MIT Lincoln Laboratory Report ACTA-5
Topic:
Summary
Automated Exposure Notication (AEN) was implemented in 2020 to supplement traditional contact tracing for COVID-19 by estimating "too close for too long" proximities of people using the service. AEN uses Bluetooth messages to privately label and recall proximity events, so that persons who were likely exposed to SARS-CoV-2 can take the appropriate steps recommended by their health care authority. This paper describes an agent-based model that estimates the effects of AEN deployment on COVID-19 caseloads and public health workloads in the context of other critical public health measures available during the COVID-19 pandemic. We selected simulation variables pertinent to AEN deployment options, varied them in accord with the system dynamics available in 2020-2021, and calculated the outcomes of key metrics across repeated runs of the stochastic multi-week simulation. SimAEN's parameters were set to ranges of observed values in consultation with public health professionals and the rapidly accumulating literature on COVID-19 transmission; the model was validated against available population-level disease metrics. Estimates from SimAEN can help public health officials determine what AEN deployment decisions (e.g., configuration, workflow integration, and targeted adoption levels) can be most effective in their jurisdiction, in combination with other COVID-19 interventions (e.g., mask use, vaccination, quarantine and isolation periods).
Summary
Automated Exposure Notication (AEN) was implemented in 2020 to supplement traditional contact tracing for COVID-19 by estimating "too close for too long" proximities of people using the service. AEN uses Bluetooth messages to privately label and recall proximity events, so that persons who were likely exposed to SARS-CoV-2 can take...
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Bluetooth Low Energy (BLE) Data Collection for COVID-19 Exposure Notification
April 13, 2022
Project Report
Published in:
MIT Lincoln Laboratory Report ACTA-2
Summary
Privacy-preserving contact tracing mobile applications, such as those that use the Google-Apple Exposure Notification (GAEN) service, have the potential to limit the spread of COVID-19 in communities; however, the privacy-preserving aspects of the protocol make it difficult to assess the performance of the Bluetooth proximity detector in real-world populations. The GAEN service configuration of weights and thresholds enables hundreds of thousands of potential configurations, and it is not well known how the detector performance of candidate GAEN configurations maps to the actual "too close for too long" standard used by public health contact tracing staff. To address this gap, we exercised a GAEN app on Android phones at a range of distances, orientations, and placement configurations (e.g., shirt pocket, bag, in hand), using RF-analogous robotic substitutes for human participants. We recorded exposure data from the app and from the lower-level Android service, along with the phones' actual distances and durations of exposure.
Summary
Privacy-preserving contact tracing mobile applications, such as those that use the Google-Apple Exposure Notification (GAEN) service, have the potential to limit the spread of COVID-19 in communities; however, the privacy-preserving aspects of the protocol make it difficult to assess the performance of the Bluetooth proximity detector in real-world populations. The...
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Fast decomposition of temporal logic specifications for heterogeneous teams
April 1, 2022
Journal Article
Published in:
IEEE Robot. Autom. Lett., Vol. 7, No. 2, April 2022, pp. 2297-2304.
Summary
We focus on decomposing large multi-agent path planning problems with global temporal logic goals (common to all agents) into smaller sub-problems that can be solved and executed independently. Crucially, the sub-problems' solutions must jointly satisfy the common global mission specification. The agents' missions are given as Capability Temporal Logic (CaTL) formulas, a fragment of Signal Temporal Logic (STL) that can express properties over tasks involving multiple agent capabilities (i.e., different combinations of sensors, effectors, and dynamics) under strict timing constraints. We jointly decompose both the temporal logic specification and the team of agents, using a satisfiability modulo theories (SMT) approach and heuristics for handling temporal operators. The output of the SMT is then distributed to subteams and leads to a significant speed up in planning time compared to planning for the entire team and specification. We include computational results to evaluate the efficiency of our solution, as well as the trade-offs introduced by the conservative nature of the SMT encoding and heuristics.
Summary
We focus on decomposing large multi-agent path planning problems with global temporal logic goals (common to all agents) into smaller sub-problems that can be solved and executed independently. Crucially, the sub-problems' solutions must jointly satisfy the common global mission specification. The agents' missions are given as Capability Temporal Logic (CaTL)...
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Quantifying bias in face verification system
April 1, 2022
Journal Article
Published in:
Comput. Sci. Math. Forum 2022, 3(1), 6
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Summary
Machine learning models perform face verification (FV) for a variety of highly consequential applications, such as biometric authentication, face identification, and surveillance. Many state-of-the-art FV systems suffer from unequal performance across demographic groups, which is commonly overlooked by evaluation measures that do not assess population-specific performance. Deployed systems with bias may result in serious harm against individuals or groups who experience underperformance. We explore several fairness definitions and metrics, attempting to quantify bias in Google’s FaceNet model. In addition to statistical fairness metrics, we analyze clustered face embeddings produced by the FV model. We link well-clustered embeddings (well-defined, dense clusters) for a demographic group to biased model performance against that group. We present the intuition that FV systems underperform on protected demographic groups because they are less sensitive to differences between features within those groups, as evidenced by clustered embeddings. We show how this performance discrepancy results from a combination of representation and aggregation bias.
Summary
Machine learning models perform face verification (FV) for a variety of highly consequential applications, such as biometric authentication, face identification, and surveillance. Many state-of-the-art FV systems suffer from unequal performance across demographic groups, which is commonly overlooked by evaluation measures that do not assess population-specific performance. Deployed systems with bias...
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Probabilistic coordination of heterogeneous teams from capability temporal logic specifications
April 1, 2022
Journal Article
Published in:
IEEE Robot. Autom. Lett., Vol. 7, No. 2, April 2022, pp. 1190-7.
Summary
This letter explores coordination of heterogeneous teams of agents from high-level specifications. We employ Capability Temporal Logic (CaTL) to express rich, temporal-spatial tasks that require cooperation between many agents with unique capabilities. CaTL specifies combinations of tasks, each with desired locations, duration, and set of capabilities, freeing the user from considering specific agent trajectories and their impact on multi-agent cooperation. CaTL also provides a quantitative robustness metric of satisfaction based on availability of required capabilities for each task. The novelty of this letter focuses on satisfaction of CaTL formulas under probabilistic conditions. Specifically, we consider uncertainties in robot motion (e.g., agents may fail to transition between regions with some probability) and local probabilistic workspace properties (e.g., if there are not enough agents of a required capability to complete a collaborative task). The proposed approach automatically formulates amixed-integer linear program given agents, their dynamics and capabilities, an abstraction of the workspace, and a CaTL formula. In addition to satisfying the given CaTL formula, the optimization considers the following secondary goals (in decreasing order of priority): 1) minimize the risk of transition failure due to uncertainties; 2) maximize probabilities of regional collaborative satisfaction (if there is an excess of agents); 3) maximize the availability robustness of CaTL for potential agent attrition; 4) minimize the total agent travel time. We evaluate the performance of the proposed framework and demonstrate its scalability via numerical simulations.
Summary
This letter explores coordination of heterogeneous teams of agents from high-level specifications. We employ Capability Temporal Logic (CaTL) to express rich, temporal-spatial tasks that require cooperation between many agents with unique capabilities. CaTL specifies combinations of tasks, each with desired locations, duration, and set of capabilities, freeing the user from...
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Wearable technology in extreme environments
March 14, 2022
Book Chapter
Published in:
Chapter 2 in: Cibis, T., McGregor AM, C. (eds) Engineering and Medicine in Extreme Environments. Springer, Cham. https://doi.org/10.1007/978-3-030-96921-9_2
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Summary
Humans need to work in many types of extreme environments where there is a need to stay safe and even to improve performance. Examples include: medical providers treating infectious disease, people responding to other biological or chemical hazards, firefighters, astronauts, pilots, divers, and people working outdoors in extreme hot or cold temperatures. Wearable technology is ubiquitous in the consumer market but is still needed for extreme environments. For these applications, it is particularly challenging to meet requirements to be actionable, accurate, acceptable, integratable, and affordable. To provide insight into these needs and possible solutions and the technology trade-offs involved, several examples are provided. A physiological monitoring example is described for predicting and avoiding heat injury. A cognitive monitoring example is described for estimating cognitive workload, with broader applicability to a variety of conditions, such as cognitive fatigue and depression. Finally, eye tracking is considered as a promising wearable sensing modality with applications for both physiological and cognitive monitoring. Concluding thoughts are offered on the compelling need for wearable technology in the face of pandemics, wildfires, and climate change, but also for global projects that can uplift mankind, such as long-duration spaceflight and missions to Mars.
Summary
Humans need to work in many types of extreme environments where there is a need to stay safe and even to improve performance. Examples include: medical providers treating infectious disease, people responding to other biological or chemical hazards, firefighters, astronauts, pilots, divers, and people working outdoors in extreme hot or...
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Correlated Bayesian model of aircraft encounters in the terminal area given a straight takeoff or landing
March 12, 2022
Journal Article
Published in:
Aerospace, Vol. 9, No.2, 12 March 2022.
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Summary
The integration of new airspace entrants into terminal operations requires design and evaluation of Detect and Avoid systems that prevent loss of well clear from and collision with other aircraft. Prior to standardization or deployment, an analysis of the safety performance of those systems is required. This type of analysis has typically been conducted by Monte Carlo simulation with synthetic, statistically representative encounters between aircraft drawn from an appropriate encounter model. While existing encounter models include terminal airspace classes, none explicitly represents the structure expected while engaged in terminal operations, e.g., aircraft in a traffic pattern. The work described herein is an initial model of such operations where an aircraft landing or taking off via a straight trajectory encounters another aircraft landing or taking off, or transiting by any means. The model shares the Bayesian network foundation of other Massachusetts Institute of Technology Lincoln Laboratory encounter models but tailors those networks to address structured terminal operations, i.e., correlations between trajectories and the airfield and each other. This initial model release is intended to elicit feedback from the standards-writing community.
Summary
The integration of new airspace entrants into terminal operations requires design and evaluation of Detect and Avoid systems that prevent loss of well clear from and collision with other aircraft. Prior to standardization or deployment, an analysis of the safety performance of those systems is required. This type of analysis...
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Robust network protocols for large swarms of small UAVs
March 5, 2022
Conference Paper
Published in:
2022 IEEE Aeropsace Conf., AERO 2022, 18 p.
Summary
In this work, we detail a synchronized channel hopping network for autonomous swarms of small unmanned aerial vehicles (UAVs) conducting intelligence, surveillance, and reconnaissance (ISR) missions in the presence of interference and jamming. The core component of our design is Queue Length Informed Maximal Matching (QLIMM), a distributed transmission scheduling protocol that exchanges queue state information between nodes to assign subdivisions of the swarm to orthogonal hopping patterns in response to the network’s throughput demands. QLIMM efficiently allocates channel resources across large networks without relying on any centralized control or pre-planned traffic patterns, which is in the spirit of a swarming capability. However, given that the control messaging must scale up with the swarm’s size and the challenging interference environments we consider, fragility could be a concern. To observe under what conditions control fails, we test our protocol against both simulated partial-band noise jamming and background interference. For the latter, we use data collected from a small unmanned aircraft system to characterize the interference seen by a UAV in the 2.4 and 5 GHz bands in both urban and rural settings. These measurements show that the interference can be 15 dB higher at a 50-meter flight altitude when compared to observations on the ground. Using this data, we conduct extensive network simulations of QLIMM in Riverbed Modeler to show that, under moderate jamming and interference, it outperforms traditional channel access methods as well as other scheduling protocols that do not pass queue state information.
Summary
In this work, we detail a synchronized channel hopping network for autonomous swarms of small unmanned aerial vehicles (UAVs) conducting intelligence, surveillance, and reconnaissance (ISR) missions in the presence of interference and jamming. The core component of our design is Queue Length Informed Maximal Matching (QLIMM), a distributed transmission scheduling...
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Radar coverage analysis for the Terminal Precipitation on the Glass Program
March 4, 2022
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-450
Summary
The Terminal Precipitation on the Glass (TPoG) program proposes to improve the STARS precipitation depiction by adding an alternative precipitation product based on a national weather-radar-based mosaic, i.e., the NextGen Weather System (aka NextGen Weather Processor [NWP] and Common Support Services Weather [CSS-Wx]). This report describes spatial and temporal domain analyses conducted over the 146 terminal radar approach control (TRACON) airspaces that are within scope of TPoG to identify and quantify future TPoG benefits, as well as potential operational issues.
Summary
The Terminal Precipitation on the Glass (TPoG) program proposes to improve the STARS precipitation depiction by adding an alternative precipitation product based on a national weather-radar-based mosaic, i.e., the NextGen Weather System (aka NextGen Weather Processor [NWP] and Common Support Services Weather [CSS-Wx]). This report describes spatial and temporal domain...
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