Y26-04-RFI_AI-Assisted_Environmental_Monitoring_&_Response.pdf

Issue Date: March 17, 2026

ORANGE COUNTY FLORIDA

PROCUREMENT DIVISION

REQUEST FOR INFORMATION #Y26-04-RFI

FOR

AI-ASSITED ENVIRONMENTAL MONITORING & RESPONSE

Copies of this Request for Information document may be obtained from Orange County by download at: https://secure.procurenow.com/portal/orangecountyfl

SUBMISSION DUE DATE:

Electronic responses will be accepted up to 4:00 PM (local time), Tuesday, March 31, 2026, via the electronic procurement portal referenced above.

Electronic submissions are required to be made through the OpenGov Procurement portal only at:

https://secure.procurenow.com/portal/orangecountyfl.

NOTICE TO RESPONDENTS:

Your point-of-contact for this solicitation is Patricia Rigby, Buyer at Patricia.Rigby@ocfl.net.

OVERVIEW:

Orange County, Florida is exploring artificial intelligence tools to enhance environmental monitoring, early detection of environmental risks, and prioritization of inspections. The County seeks information from vendors capable of analyzing environmental data, sensor streams, and imagery to identify potential water quality issues, harmful algal blooms, and other environmental concerns in order to support faster response and proactive environmental protection.

NO AWARD WILL BE MADE FROM THIS SOLICITATION.

THIS IS A REQUEST FOR INFORMATION ONLY

https://secure.procurenow.com/portal/orangecountyfl mailto:Patricia.Rigby@ocfl.net

REQUEST FOR INFORMATION

RESPONSE FORM AND MARKET/PRODUCT QUESTIONNAIRE

RESPONSE FORM

THE FOLLOWING SECTION MUST BE COMPLETED BY ALL RESPONDENTS:

Company Name:

(Street No. or P.O. Box Number) (Street Name) (City)

(County) (State) (Zip Code)

Contact Person:

Phone Number:

Email Address:

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MARKET/PRODUCT QUESTIONNAIRE

1. VENDOR BACKGROUND AND EXPERIENCE

a. Describe your organization’s experience implementing AI or advanced analytics solutions for environmental monitoring, including water quality, stormwater management, or ecological protection.

b. Provide examples of deployments with local governments, environmental agencies, or utilities.

c. Provide case studies demonstrating how AI solutions have improved environmental monitoring, incident detection, or regulatory compliance.

d. Identify any experience supporting water quality monitoring, harmful algal bloom detection, stormwater inspection prioritization, or watershed management.

2. SYSTEM CAPABILITIES

Environmental Monitoring

a. Describe how your solution collects and analyzes environmental data from sources such as:

o water quality sensors o satellite imagery o aerial imagery or drones o environmental reports from residents o historical environmental monitoring data

b. What types of environmental indicators can the system detect or monitor (e.g., nutrient levels, turbidity, algae bloom indicators, stormwater runoff patterns)?

c. Can the solution support real-time or near-real-time monitoring of environmental conditions?

AI-Based Risk Identification

d. Describe how AI models identify potential environmental risks or anomalies, such as emerging water quality concerns or algae bloom conditions.

e. Can the system analyze historical environmental data to predict areas of elevated environmental risk?

f. Does the platform provide early warning alerts to environmental staff when conditions indicate potential environmental incidents?

Inspection Prioritization

g. Describe how the solution can assist in prioritizing field inspections based on environmental risk factors.

h. Can the system automatically identify locations that may require investigation or enforcement actions?

i. Does the platform support automated task assignment or inspection scheduling based on risk analysis?

3. DATA SOURCES AND INTEGRATION

a. Describe integration capabilities with existing environmental monitoring systems, water quality databases, or GIS platforms.

b. Can the system integrate with county GIS systems to visualize environmental risks geographically?

c. Can the solution ingest data from IoT environmental sensors or monitoring equipment?

d. Does the system support integration with drone imagery or satellite data sources?

4. AI MODEL GOVERNANCE AND TRANSPARENCY

a. What AI techniques power the environmental monitoring solution (e.g., machine learning, computer vision, predictive analytics)?

b. How does the system ensure accuracy when identifying environmental risks or anomalies?

c. Can the system provide explainable insights or supporting data for AI-generated alerts?

d. What mechanisms allow environmental staff to review, validate, or override AI-generated findings?

5. SECURITY AND DATA MANAGEMENT

a. Describe how the system manages environmental monitoring data and associated imagery.

b. What cybersecurity protections exist for government data and sensor networks?

c. What compliance standards does the solution support (e.g., SOC 2, FedRAMP, or other government security frameworks)?

6. IMPLEMENTATION AND DEPLOYMENT

a. What is the typical deployment timeline for an AI-based environmental monitoring system?

b. What infrastructure or equipment may be required to support implementation (e.g., sensors, drones, cloud services)?

c. What data sources would the County need to provide for initial model training?

d. What training is required for environmental staff and system administrators?

7. PERFORMANCE METRICS AND REPORTING

a. What key performance indicators are typically used to measure success for environmental monitoring AI systems?

b. Can the system provide reporting on:

o environmental incidents detected o response times o inspection prioritization effectiveness o environmental trend analysis

c. Can the system generate visual dashboards for environmental monitoring and decision-making?

8. COST AND PRICING

a. Provide estimated cost ranges for implementation at a county scale.

b. Describe your pricing model (subscription, sensor-based licensing, or usage-based).

c. Identify ongoing operational, maintenance, or data service costs.

9. INNOVATION AND FUTURE CAPABILITIES

a. Describe emerging capabilities such as:

o AI-driven watershed modeling o predictive environmental compliance analytics o automated drone monitoring o climate resilience modeling

b. How could the solution support long-term environmental planning or climate adaptation strategies?

10. PILOT PROGRAM OPPORTUNITIES

a. Would your organization support a pilot deployment focused on selected water bodies or environmental monitoring zones?

b. What resources would be required from the county to conduct a pilot?

c. What evaluation metrics would you recommend for measuring pilot success?

REQUEST FOR INFORMATION #Y26-04-RFI