Edward Knightly http://knightly.rice.edu High Resolution Sensing and Real-time Communication for Urban Environmental Hazards Edward Knightly http://knightly.rice.edu

Application Drivers: Urban Real-time Environmental Sensing Problem Urban chemical and industrial plants Nearby low-income communities at risk Emergencies: residents learn of hazardous leaks and extreme events via news casts: “shelter in place” Valero refinery near Houston, TX Chevron refinery in Bay Area, CA

2012 Chevron Fire in Richmond, California Extreme Events 2016 Dupont leaked 24,000 pounds of methyl mercaptan in La Porte, Texas 4 workers died, investigation ongoing 2012 Chevron Fire in Richmond, California 15,000 hospitalized Dupont claimed 100 pounds $2M fine, 210 arrests

Limits of Today’s Sensors Current air quality assessment is coarse grained Spatial: city average Temporal: daily Composition: ozone and NO2 only Limited actionability

Application Drivers: Urban Real-time Environmental Sensing Objectives Empower communities near environmental hazards with real-time actionable information High resolution data sets to foster environmental justice Proof of concept at Technology For All Technological goals Gas sensor network with high spatial, spectral, and temporal resolution Real-time data collection, communication, and processing

Laser Wavenumber (cm-1) Rice Sensor Absorption Laser Wavenumber (cm-1) Laser spectroscopy Pollutants have spectral signature Identify chemical and concentration Internal reflectors to increase resolution

Road Map Commoditizing laser spectroscopy Data science Real-time processing of air quality spectrum Actionable alerts & minimum false positives Networking feedback loop Wirelessly stream high resolution data sets Cloud data processing High resolution data for scientists, plant, and first responders Location-based alerts for community

Wireless Challenges Faster, farther, lower latency, more ubiquitous Data rate: break the Tb/sec barrier Spectrum: diverse and wideband from MHz to THz Density: bits/sec/Hz/m2 Latency: avg and tail

New Performance Metrics Asymmetry Minimize client requirements form factor, communication, computation, energy efficiency Via advanced infrastructure Scalability Air time efficiency reduction per incremental node Robustness to mobility Throughput reduction with “nomadic” baseline

Rationale for Enabling Technologies Massive MIMO for capacity scaling Infrastructure has sophisticated signal processing, plug in power source, and large array Mobile clients and sensors are constrained single antenna, energy efficiency, etc. Diverse spectrum for robust availability No ‘one size fits all’ spectrum UHF, ISM, 3.5 GHz, 60 GHz, and more New rate/range design space

Rice Platform and Plan Goals Scalable and flexible h/w and s/w platform to explore the design space Protocols and algorithms at all layers Experimental evaluation in real-world propagation environments with sensor applications

Summary Driving applications Diverse performance metrics High resolution environmental sensing Diverse performance metrics bits/sec/Hz/m2 to air-time-efficiency scaling Open challenges Clean slate design to operational experience