Transcript Highlights:

• </c> Representative Sensor Murray. Representative Sensor Murray.
• Uh, the complainants are Leader Long and Representative Sensor Murray.
• Uh, the complainants are Leader Long and Representative Sensor Murray.
• Uh, the complainants are Leader Long and Representative Sensor Murray.
• </c> Sensor Moore or I take lightly. Sensor Moore or I take lightly.

Keywords: 1183, house

Transcript Highlights:

• This is Representative Sensor Mura. I apologize.
• This is Representative Sensor &gt;&gt; Sorry.
• This is Representative Sensor Mura. I apologize.
• Um what I'm Representative Sensor Mura.
• >> To, uh, Madame Chair, Representative Sensor, to get to a process like that?

Keywords: 1183, house

Transcript Highlights:

• And I recognize the member from Hennepin, Representative Sensor Meera. Thank you, Madam Speaker.
• the member from<00:04:02.720><c> Henipin,</c><00:04:03.519><c> Representative</c><00:04:04.239><c> Sensor
• </c> from Henipin, Representative Sensor from Henipin, Representative Sensor Meera.

Keywords: 1183, house

Transcript Highlights:

• I recognize the member from Hennepin, Representative Sensor Meera. engagement with Taiwan based on the
• And I recognize the member from Hennepin, Representative Sensor Meera. Thank you, Madam Speaker.
• the member from<00:13:56.240><c> Henipin,</c><00:13:57.120><c> Representative</c><00:13:57.839><c> Sensor
• </c> from Henipin, Representative Sensor from Henipin, Representative Sensor Meera.

Keywords: 1183, house

Transcript Highlights:

• The last time we've had people out, if they've located faulty sensors, they've said the systems are so
• The last time we've had people out, if they've located faulty sensors, they've said the systems are so
• , we can't purchase any of those sensors or anything else anymore for those systems.
• Again, we have glass-break sensors and all sorts of different sound and motion sensors throughout the
• Because it is the crime laboratory and we have evidence, even if we think it may be a faulty sensor,

Summary: The committee met to review the Attorney General’s budget and related agency operations, beginning with Legislative Council staff walking members through compliance reports and a blue-sheet base budget document. Staff highlighted current-biennium items such as FTE changes, one-time appropriations, litigation funding, opioid settlement receipts, continuing appropriations, and major special and federal funds. Members asked for clarification on items including the Missing Indigenous People Grant Fund, the Internet Crimes Investigation Fund, and the Medicaid Fraud Control Unit grant funding. Assistant Attorney General Clare Ness then gave an overview of the office’s structure, staffing, and budget pressures. She emphasized the office’s broad statutory duties, the value of its legal services to state and local government, and concerns about attorney pay lagging behind other agencies. Members discussed whether attorney compensation should be benchmarked more consistently across state government and whether some legal work could be consolidated within the AG’s office. Ness also addressed questions about AG opinion turnaround times, boards-and-commissions training, the new-and-vacant FTE pool, operating expense cuts, office leases, and the state’s criminal justice information systems. The crime lab presentation drew significant attention. Director Jennifer Penner described severe space, safety, and infrastructure problems at the current lab, including cramped work areas, glycol leaks, outdated fire and burglar alarms, air-handling limits, and equipment failures that have delayed toxicology work. She said the 2024 study projected a much larger facility would be needed and that the preferred location would be near the current health department site, but in a new building. Members asked about possible evidence risks, backlog status, and whether the proposed building would solve the current problems; Penner said it would and noted backlogs have improved overall, though some delays remain. The committee also heard from the new Medicaid Fraud Control Unit director, who described the unit’s civil and criminal work, federal-state funding split, and examples of fraud such as billing for services not provided or upcoding. The gaming division reported continued growth in charitable gaming and e-tabs, with members expressing concern about large trust-account balances, site competition, and possible misuse of proceeds. Finally, BCI outlined its caseload, cybercrime work, missing Indigenous persons task force, and the surge in CSAM cyber tips; members asked about AI-generated CSAM, and the AG’s office noted that last session’s law increased penalties and expressly allowed AI-generated CSAM to be prosecuted like other CSAM. No formal votes or actions were taken beyond approval of the minutes.

Transcript Highlights:

• or insulin pumps just examples sensors or insulin pumps just examples or<00:33:59.000><c> to</c><00:
• Glucose sensors. Close parenthesis.
• </c><01:32:18.199><c> sensors</c><01:32:19.119><c> close</c> glucose sensors sensors close glucose sensors
• and parentheses or disabilities sensors and parentheses or disabilities from<01:33:08.880><c> using<
• <01:54:06.320><c> closed</c><01:54:06.719><c> parentheses</c><01:54:07.520><c> or</c> sensors closed

Keywords: 928, house, all

Summary: The subcommittee work session of the Education Policy and Administration Committee focused on House Bill 131 and House Bill 781, which were described as nearly identical bills addressing student cell phone use in schools. Members noted that HB 781 is an early bill and therefore needed committee action by Wednesday, while HB 131 did not face that deadline. The chair and members discussed the bills’ shared goal of requiring school boards to develop and adopt policies on student personal device use, with debate over whether the state should set minimum standards or leave more to local control. A major topic was funding. One member urged the committee to avoid creating an unfunded mandate and asked for some funding support, while others argued it was too early to commit money and that the committee should first establish the policy framework. The governor’s proposed funding was discussed, including a $1 million figure in the budget and a separate $250,000 amount referenced in the bill, but several members said the money would likely be insufficient to cover all students or pouch systems statewide. The committee also reviewed a handout reflecting proposed budget language that would require school boards to adopt policies on personal device use during the school day, with schoolwide implementation and exceptions for medical disability or language proficiency needs, and a DOE-administered grant program. Members spent considerable time on drafting details, especially deadlines and exceptions. They debated whether the bills should require school boards to “develop,” “adopt,” or also “implement” policies, and whether the effective date of the act should also serve as the deadline for school boards. They also discussed whether exceptions for classroom instructional use should be mandatory or merely encouraged, and whether the bills should explicitly include or exclude charter schools. Additional proposed exceptions included IEPs, 504 plans, English learners, and medical needs such as glucose sensors or insulin pumps, with some members suggesting medical issues be certified by a physician. No final vote or formal action was taken in the work session.

Transcript Highlights:

• One of the few things we can do is clean our sensors using air, and so we can trigger a blast of air
• to clean the sensors.
• But if we do lose vision, we do have a degraded capability, whether it be sensor capability or compute
• that particular sensor are being leaned on.
• And so that's why you have a diverse sensor stack that you can depend upon in different circumstances

Transcript Highlights:

• </c><00:17:46.039><c> mura</c> Council as representative sensor mura Council as representative sensor
• </c> thank you uh Representative Sam sensor thank you uh Representative Sam sensor mura<00:25:36.000>
• </c><00:30:42.080><c> M</c><00:30:42.440><c> with</c><00:30:42.600><c> that</c> representative sensor
• M with that representative sensor M with that representative<00:30:43.279><c> sensor</c><00:30:43.559
• M REM renews her representative sensor M REM renews her motion<00:30:45.159><c> that</c><00:30:45.360

Bills: HF1966, HF54, HF2043, HF1171, HF2741

Keywords: HF1966, Minnesota Association of Alternative Programs, STARS program, alternative education, alternative programs, education finance, general fund appropriation, student support services, career readiness, employment skills, academic skills, social skills, student conferences, training grants, Minnesota Department of Education, specialized education, at-risk students, nontraditional education, HF54, Silver Lake

Transcript Highlights:

• Sun to give more information on the MUST sensor. Cool. Thank you, Grayson. MUST sensor. Cool.
• What's unique about this MUST device is that it brings all those kinds of sensors you see on the screen
• the digital representation of the roadway infrastructure and also the live data collected from the sensor
• Just very briefly, if you'd like to know or have any other questions about the MUST sensor, we've got

Summary: The Senate Transportation Committee met in Yakima to focus on tribal traffic safety, with members and Yakima Nation leaders emphasizing the importance of safety, the right to travel, and continued partnership on U.S. 97 corridor improvements. Yakima Nation Vice Chair Christopher Wallachie and engineering staff described the Tribal Traffic Safety Committee, the U.S. 97 safety project, heritage connectivity trails, roundabout construction, and the use of federal grants and advanced sensing technology to identify hazards before crashes occur. They highlighted collaboration with WSDOT, the Traffic Safety Commission, the University of Washington, and other regional partners, and explained that the goal is to move from reactive crash response to proactive risk reduction. The Yakima Nation engineering team and AI Vision presented the MUST sensor project, which uses compact AI-enabled devices to collect traffic counts, speeds, near-miss events, roadway conditions, and pedestrian activity, with data transmitted to a dashboard and used for real-time warnings and longer-term planning. Committee members asked about speed tracking, driver behavior, enforcement, and partnerships with WSDOT and counties. Yakima Nation staff said the relationship with WSDOT has improved over time, especially after community outreach on proposed roundabouts, and that the tribe now supports several roundabout projects and broader safety coordination. The Washington Traffic Safety Commission then presented statewide fatality trends and tribal traffic safety data. Mark McKekney said 2024 showed a roughly 10% decrease in fatalities statewide, though recent years remain among the highest in decades. He noted that race and ethnicity data are only available for people who die in crashes, and that many American Indian and Alaska Native fatalities involve passengers, pedestrians, or bicyclists rather than drivers. Penny Rerick outlined tribal traffic safety coordinator grants and other state-funded tribal projects, including work with Yakama Nation, Colville, Kalispel, Makah, Port Gamble S'Klallam, Muckleshoot, Lower Elwha, and Puyallup, stressing that flexible state funding helps fill gaps left by federal programs and supports community-led solutions. The final presentation covered impaired driving enforcement and ignition interlock compliance in Yakima County. Yakima Police Chief Sean Boyle said the city created a DUI enforcement and education officer program that helped reduce serious injury and fatal impaired-driving crashes, supported by state funding and social media outreach. Yakima County District Court’s Nick Bazan described a supervision program for DUI offenders and interlock compliance, reporting more than 1,000 DUI convictions in 2024-25 and about 3,800 noncompliant interlock users countywide. He said the court is using a two-pronged approach—pretrial assistance for indigent clients and post-conviction accountability and case planning—to improve compliance and reduce impaired driving. The committee expressed support for the work, noted the progress made, and adjourned the work session after thanking presenters for their updates.

Transcript Highlights:

• </c> &gt;&gt; Uh Representative Sensor Meera. &gt;&gt; Uh Representative Sensor Meera.
• Representative Sensor apprehended? Representative Sensor Meera. Meera. Meera.
• I really representative sensor Mura.
• Representative<01:41:17.520><c> Sensor</c><01:41:17.840><c> Mira.</c> Representative Sensor Mira.
• Representative Sensor Mira.

Bills: HF4077, HF3798, HF3886

Keywords: municipal nondisclosure agreement, NDA, public records, transparency, local government, county, city, town, school district, housing and redevelopment authority, economic development authority, port authority, economic development, land development, public financing, tax increment financing, TIF, abatement, municipal bonds, debt obligations

Transcript Highlights:

• There's weather sensors and all kinds of things. We actually just took delivery of our first one.
• ><c> all</c><00:41:56.640><c> kinds</c><00:41:56.880><c> of</c> There's weather sensors and all kinds
• of There's weather sensors and all kinds of things.<00:41:57.280><c> We</c><00:41:57.440><c> actually
• How do we get our weather sensors to detect the weather in this small space between 500 feet and 1,500
• How do we get our weather sensors to detect the weather in this small space between 500 feet and 1,500

Keywords: 958, all

Summary: The task force approved the October 14, 2025 meeting minutes and then heard a presentation from Austin Kaylor of WSP on alternative aviation fuels. Kaylor described an ongoing feasibility study focused on Cincinnati/Northern Kentucky International Airport and the other four commercial airports in Kentucky, with an eye toward both near-term use of alternative aviation fuel in existing supply chains and longer-term in-state production using local feedstocks. He said Kentucky’s current jet fuel use at the five airports is about 609 million gallons annually and could approach 1 billion gallons by 2050, and he outlined potential feedstocks such as soybeans, corn, and waste oils, along with existing logistics assets like river terminals, trucking, rail, and some pipelines. He also discussed federal and state policy support, including renewable fuel credits and the recent 45Z tax credit extension, and said the study suggests significant economic-development potential if Kentucky can leverage existing infrastructure and incentives. Members asked about the cost of sustainable aviation fuel, whether taxpayers would be subsidizing it, and whether food crops would be diverted from food use. Kaylor responded that the market is increasingly using second-generation and waste-based feedstocks, that federal incentives can cover much of the price differential, and that SAF is a direct substitute for conventional jet fuel with some efficiency benefits. He said demand comes from both U.S. and foreign carriers, including major U.S. airlines that have made emissions-reduction commitments. Members also raised the possibility of locating production in Appalachia to create jobs closer to feedstock sources; Kaylor said that approach has worked in other states and could fit Kentucky’s logistics network. The committee then heard from Leif Elder of the Utah Department of Transportation, who introduced himself and said he would discuss advanced air mobility legislation in Utah. The transcript cuts off before his substantive presentation, and no further votes or actions were recorded after the question-and-answer discussion on alternative aviation fuels.

Transcript Highlights:

• 05:18.720><c> present</c><00:05:19.440><c> Hill</c><00:05:19.960><c> present</c><00:05:20.759><c> sensor
• </c> hill hill present Hill present sensor hill hill present Hill present sensor mura<00:05:23.160><c
• > sensor</c><00:05:23.680><c> mura</c><00:05:24.080><c> present</c><00:05:24.720><c> censor</c><00:05

Keywords: 1183, house

Transcript Highlights:

• ><c> talking</c> Representative Sensor, are you talking Representative Sensor, are you talking about<
• </c><00:49:07.440><c> Mura,</c><00:49:07.760><c> I</c> with you, Representative Sensor Mura, I with you
• </c><00:50:08.880><c> Representative</c><00:50:09.440><c> Sensor</c> &gt;&gt; Represent excused.
• Representative Sensor &gt;&gt; Represent excused.
• Representative Sensor Mura, Mura, Mura, &gt;&gt; no. &gt;&gt; no. &gt;&gt; no.

Keywords: 1187, senate, all

Transcript Highlights:

• Hot wheel detectors are infrared sensors for wheel temperature.
• Most of these detectors would be co-located for multi-sensor validation and reduced false positives.”
• Hot wheel detectors, infrared sensors Hot wheel detectors, infrared sensors for<01:06:16.000><c> wheel
• </c> co-located for uh multi-sensor co-located for uh multi-sensor validation<01:06:46.960><c> and</c
• </c> detectors and sensors themselves. detectors and sensors themselves.

Keywords: 1187, senate, all

Transcript Highlights:

• :40:45.520><c> wind</c> marshall, deployed wildfire and wind marshall, deployed wildfire and wind sensors
• 46.960><c> we</c><00:40:47.119><c> have</c><00:40:47.280><c> early</c><00:40:47.599><c> alert</c> sensors
• statewide so we have early alert sensors statewide so we have early alert capabilities<00:40:48.800>
• </c><00:51:44.000><c> that</c><00:51:44.240><c> I</c> happen again, including sensors that I happen again
• , including sensors that I mentioned<00:51:44.640><c> and</c><00:51:44.800><c> emergency</c><00:51:45.200

Keywords: 910, house, all

Transcript Highlights:

• ,</c><00:34:04.480><c> AI</c> understands software, sensors, AI understands software, sensors, AI systems
• &gt;&gt; Representative<01:12:47.199><c> Sensor</c><01:12:47.600><c> Meera.
• </c> &gt;&gt; Representative Sensor Meera. &gt;&gt; Representative Sensor Meera.
• Representative Sensor Meera has &gt;&gt; Perfect.
• Representative Sensor Meera. >> No. Representative Scraa. >> Hi.

Keywords: 1183, house

Transcript Highlights:

• Representative Sensor<01:12:23.800><c> Mira.</c> Sensor Mira. Sensor Mira.
• </c><01:14:12.000><c> Mira</c> question Representative Sensor Mira question Representative Sensor Mira
• </c><01:14:33.200><c> Thank</c> Representative Sensor Mira. Yeah. Thank Representative Sensor Mira.
• And the Representative Sensor Mira.
• Representative Sensor Mira. Yes. Yes. Representative Sensor Mira. Yes.

Bills: HF3119

Keywords: teacher compensation, educational staff, unlicensed staff, minimum wage, inflation adjustment, education finance, 1183, house

Transcript Highlights:

• I'm in Representative Sensor Mira: Thank you, Chair West, for bringing this up.
• Representative<00:28:20.360><c> Sensor</c><00:28:20.679><c> Mira.
• Is there a Representative Sensor Mira.
• Representative<00:29:12.000><c> Sensor</c><00:29:12.400><c> Mira.</c> Representative Sensor Mira.
• Representative Sensor Mira.

Keywords: 1183, house

Transcript Highlights:

• Often this causes damages not only to the exterior of the vehicle, but can interfere with sensors now
• You'll notice that I've circled the sensors, the adapter cruise control where the front camera is, you'll
• many states over and it took about 4 or 5 weeks to get and they drilled holes and it ruined the the sensors
• happened at the federal level for, for motor carriers to be able to develop a product with those front sensors

Bills: HB 408, HB 787, HB 1029, HB 1126, HB 1136, HB 1607

Keywords: cultural attractions, highway signs, Texas Department of Transportation, travel guidance, Museum of the Big Bend, traffic control, tourism, sunscreening devices, motor vehicle, judicial specialty license plate, vehicle safety, Texas Transportation Code, disability, parking, Governor's Committee, mobility impairment, disabled veterans, legislative recommendations, license plates, vehicle registration

Transcript Highlights:

• Maybe Representative Sensor M. I've asked you to introduce; we don't know the name. Yuna.
• transportation baby's name uh<00:10:09.959><c> maybe</c><00:10:10.360><c> representative</c><00:10:10.880><c> sensor
• </c><00:10:11.279><c> M</c><00:10:11.920><c> I've</c> uh maybe representative sensor M I've uh maybe
• representative sensor M I've asked<00:10:12.200><c> you</c><00:10:12.279><c> to</c><00:10:12.480><c>

Keywords: 1183, house