New York Tech Journal
Tech news from the Big Apple

HardwiredNYC: #drones, #AmazonEcho, #SmartLuggage, #SmartCities

Posted on April 5th, 2016

#HardwiredNYC

04/05/2015 @WeWork, 115 W 18th Street, NY

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The following speakers presented

Brian Streem @Aerobo (build and service drones) talked about the drone market. After showing two videos: Chromaticity and Paint the Sky (about the shooting of Chromaticity), Brian spoke about

  1. The Aerobo mini – a lightweight drone designed to provide live broadcast quality feeds which can be transmitted up to 3 miles.
  2. They have a 333 exemption from regulation which is required to commercially fly a drone in the U.S. They anticipate new FAA rules that may relax some of the current requirements, such as requiring a pilot’s license for commercial flights. Also he anticipates that a category of micro UAVs will be created with alternative licensing requirements.

Next, Donn Morrill @AmazonEcho talked about the hardware and software of the echo and how Amazon is targeting it to be the center of smart home integration. He provided some insights into the design philosophy of the software including

  1. They will probably not release tools to analyze the tone, volume, speed of speech detected by the API since they are sensitive to user experience and want to product the brand
  2. In a similar vein, they do not plan to allow skills to be self-initiating (all skills require you to initiate the conversation) to avoid verbal spam.

Next, Matt Turck interviewed John Udashkin  & Justin @Raden (luggage with a battery and Bluetooth). Justin initiated the product following extensive travel experience when he worked in the fashion industry. Fashion dictated the design of a product with simple lines as in the iPhone and Beats.

Justin and John noted

  1. Justin researched the luggage industry under the tutelage of a retired executive at Tumi.
  2. This contact allowed him to gain credibility when looking for a manufacturing partner
  3. They chose VC over crowd funding for its greater flexibility
  4. John formerly worked at Quirky, so he had the manufacturing contacts needed for the electronics
  5. Integrated the electronics was difficult since luggage and electronics factories are very different: luggage factories are larger and dirtier, electronics factors are smaller and emphasize cleanliness.
  6. They were careful to avoid problems passing air transport security such as limiting the size of the battery and making it removable. Also wiring and Bluetooth can be accessible if the bag is inspected.
  7. They eventually see their app as a full utility platform with information such as TSA wait times, real time flight updates, etc.
  8. They are looking beyond online sales and see the advantages of retail outlets such as malls.
  9. Their product can be seen at a popup store at 72 Spring Street, NY

They also talked about pivots during development

Design change. They tested a biometric lock, but found it was not useful and can create electronics issues since luggage gets knocked around.

The electronics enclosure was originally different, but it suffered damage & wire breakage. The eventual design has a strong backplate to shock proof and water proof the electronics.

Finally, Joao Barros @Veniam talked about the communication network developed in Porto, Portugal (also known for the elegant arch-truss bridge constructed there by Gustav Eiffel). Porto has a mesh network consisting of wi-fi hotspots supplemented by hot spots in vehicles. These hotspots allow seamless integration of wi-fi, cellular and 5.9GHz networks.

Joao said that vehicles offer an ideal platform for hotspots

  1. They are mobile so they can collect data throughout the city = smart city
  2. Their batteries are recharged by the engine
  3. They are large enough that it is not an inconvenience to have a box large enough to hold multiple communications devices
  4. They can provide in-vehicle entertainment
  5. They can be used as an emergence communications backup for other systems
  6. They can be used to avoid vehicle collisions

The key technology is the ability to perform seamlessly handoffs across different networks (wi-fi, cell, 5.9GHz).

Specific applications are sensors of garbage cans indicating when they have already been emptied and heart rate monitoring of drivers indicating issues on the roads.

The system is also installed in Singapore and they will soon announce a rollout in the U.S.

posted in:  hardware, Hardwired NYC, Natural User Interface, NYC smart city and energy data, startup, UX    / leave comments:   No comments yet

SQUID – automating the detection of #potholes in #NYC

Posted on March 28th, 2016

#NYsmartCityData

03/28/2016 @ UrbanFutureLab, 15 MetroTech, 19th fl, Brooklyn, NY

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Varun Adibhatla @Advanced Research in Government Operations (@ARGO) talked about their initiative to more quickly map the potholes in NYC’s 6000 miles of roads.

Monitoring is currently done by a dedicated group (Scout – street condition observation unit) that does “windshield surveillance” of all roads. Varun’s group is working an automated system which sends accelerometer data and pictures to the cloud. The accelerometer indicates street hot spots and the images can be scanned or serve as verification of the problem.

SQUID (street quality identification device) is run by a Raspberry Pi that is attached inside the trunk with a camera mounted next to the backup camera. Data are streamed to the cloud with one 15kb per image * one image per second. In their trials they drove 400+ miles in a week and collected 10 gig of data.

Next Varun showed an interactive map powered by Tableau that highlights the bumpy routes and allows one select images taken of the road.

Finally he talked about future initiatives including

  1. Anticipatory maintenance
  2. Using microphones to records street noise as a classifier for potholes
  3. A smartphone app that crowd sources street condition data to the cloud
  4. Adding air quality sensors to provide a more complete picture of the environment

He recommended the book ‘Smart Cities’ by Anthony Thompson as a consumer handbook for smart cities globally.

posted in:  Internet of Things, NYC smart city and energy data    / leave comments:   No comments yet

#CivicHacking

Posted on January 26th, 2016

#NYCSmartCities & #EnergyData

01/26/2016 @UrbanFuturesLab, 19th floor, 15 MetroTech, Jay Street, Brooklyn

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David Moore @PPF spoke about his organization’s projects to make it easier to access/track legislation at the Federal, state and local levels. The NY City Council has a web site, but it’s hard to find information. #Councilmatic provides a user-friendly interface that can be searched by committee meetings, your council member, bills being heard, etc. The site makes it easier to find all proposed legislation on an issue, track the hearings on the bill, submit comments to council members, etc.

NYC.councilmatic.org covers the New York city council and was launched on Sep 30, 2015. They have similar sites for Chicago and Philadelphia. PPF is acquiring the resources to add other U.S. cities.

Earlier, David created the OpenCongress site which is a user friendly interface on federal bills including bill summary, annotate bill text, etc. The data were acquired by screen scraping public sites.

Next, OpenState created similar sites for each state.

The Sunlight foundation provided some funding for these ventures, but now concentrates only on the Federal and State level. PPF concentrates on cities.

To standardize their data presentation, PPF also created a data standard: Open civic data.

posted in:  data, NYC Energy Data, NYC smart city and energy data, Open source    / leave comments:   No comments yet

#Energy, #Data, #Buildings: taking back the power

Posted on December 9th, 2015

NYC Smart City

12/09/2015 @ConsolidatedEdison, 4 Irving Place, NY

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Lucas Finco moderated a discussion on initiatives to modernize the energy grid in New York City. The discussants were John Shipman from ConEd, Jeremiah Miller from Smarter Grid Solutions, and Nicholas Davis from GridMarket.

Major points discussed included

  1. How incentives drive the market to provide more power to New York without adding capital investments to cover higher peak demands. This means an emphasis on reducing peak demand using systems such as batteries, thermal storage, chillers, etc. The emphasis has been on locations with the least amount of head room as in the Brooklyn-Queens demand program.
  2. Increased alternative electricity production also requires a reconsideration of the risks to the overall system as more reliance is placed on 3rd party generators of electricity and off-grid storage by individuals/companies using batteries. Overall system reliability and production quality (harmonics on the grid) are some considerations.
  3. How can ConEd move toward a model in which they control the overall distribution of power, but much of the generation and distribution is handled by others?
  4. Can an electricity company make money by selling production/usage data about its network? What privacy issues are involved? Could data be used to estimate the number of TVs in a household and when they need to be upgraded?
  5. What is the timing of incentives? How do we avoid giving incentives such as those given from CFL light bulbs. CFLs (pollution and performance issues) were quickly replaced by LED bulbs which are economically viable without incentive.
  6. What is the right level of incentive to encourage alternative electricity generation and storage?
  7. How can one accurately predict future needs given the rapidly changing technologies of electric cars, batteries, grid management, etc.

 

posted in:  data, NYC smart city and energy data    / leave comments:   No comments yet

Actuating human behavior in small cities

Posted on October 21st, 2015

NYC Smart City and Energy Data

10/21/2015 @Urban Future Labs, 15 MetroTech, Brooklyn

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Matt Caywood @TransitScreen spoke about using information dissemination as a method to increase use of #PublicTransit.

He first noted the high cost of #transportation and the added costs of inefficiencies (such as traffic congestion) in the transportation network. In addition, efforts to remove these inefficiencies by adding supply have a mixed, and often counterproductive, outcome. As example of the failure of this approach he cited a freeway in Houston who’s “improvement” in 2014 slowed traffic by 33%, encouraged city sprawl and induced additional demand.

By contrast, his firm emphasized Transportation Demand Management (TDM) in which riders are encourage to move from one form of transportation to another or commute at off-peak times. (One very effective example of #TDM is congestion pricing)

TransitScreen focuses on increasing the availability of real-time public transit information. They place real-time transit screens in public locations and on mobile devices. The goal is to move the information out of the train stations and into buildings so riders can better plan their trips.

He cited several studies showing the benefits of providing better transit information.

  1. The Wilson Boulevard corridor in Arlington, VA showed an increase to 47% use of public transit by publicizing the availability of public transit.
  2. Real-time information at stations for buses
    1. NYC indicate 1.7% increase in ridership on routes
    2. Chicago significant but modest increase
    3. Tampa no significant effect
    4. But all showed improved rider satisfaction as measured by perceived reliability, convenient, more control, shorten wait time

Placing of screens outside the train stations has shown benefits

  1. Parkmerced in San Francisco replaced ads with real-time transit screens in the building lobbies and has seen increased viewer engagement along with a 5% decrease in driving.
  2. Seattle Children’s hospital has a transit screen in the lobby. Interaction increased as the coffee shop in the lobby saw a 33% increase in transactions after the screen was put in place.
  3. Barclays Center, Brooklyn saw a 9% shift to public transit based on increased publicity of available transit options in a survey of likely Nets game attendees

TransitScreen also studied the Capital Bikeshare program in D.C. advising riders on the probability of a bike arriving in the next 5 minutes to add to an empty bikeshare station.  They also computed the probably of a bike being available 5 minutes from now when there is only a single bike in the station now. The probabilities were computed for different times, days of the week and weather conditions.

Matt talked about the difficult of switching one’s default mode of transportation and how better information can help. In honor of the anniversary of “Back to the Future”, the Guardian had an article elaborating on the challenges of changing transportation modes for society as a whole.

 

posted in:  NYC Energy Data, NYC smart city and energy data    / leave comments:   No comments yet

Challenges and Opportunities of #HVAC Data – Gabriel from Ecorithm  

Posted on June 24th, 2015

NYC smart city and energy data #smartcitydata

06/23/2015 @Urban Futures Lab, 15 MetroTech, 19th Floor, NY

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Gabriel Peschiera @ Ecorithm (a software startup that turns building data into actionable insights) spoke about the challenges of collecting and analyzing sensor data within large buildings. These analyses have the potential to improve the comfort of the occupants and the functioning of the building systems.

Ecorithm focuses on buildings with more than 100,000 sq ft of floor space. These buildings have a building maintenance system to monitor the function of the chiller -> air handlers -> Variable Air Volume

In older systems, they will work with 3rd parties to place sensors for input into JACE, the Java Application Control Engine. For newer systems, they will collect data from the current BMS. In a typical building, their system receives information from 3000 locations, with sensor readings every 5 minutes. Data are available at the end of each day.

Gabriel touched on some of the data analysis tools and challenges

  1. Data cleaning problems often center around mislabeled locations and types of sensor inputs
  2. Spectral analysis in frequency space shows the temperature fluctuations driven by daily schedules, control loops and weather. From frequency plots they can see periodic patterns that might indicate persistent problems. They can also see if disparate locations have similar frequency patterns which may be driven by a common source.
  3. Support vector regressions can detect nonlinear deviations from expected patterns. This method can be used to detect faults and fill in missing data.
  4. Model-based optimization may eventually be a technology to better tune systems.

He also presented screen shots of their monitoring control panel and fault reports.

posted in:  NYC Energy Data, NYC smart city and energy data    / leave comments:   No comments yet