Bridge Project · Badakhshan, Afghanistan · 36.99°N 70.28°E
Established2017
HeadquartersArlington, Virginia, USA
SectorsAI - Unmanned Systems - Global Health - Agriculture - Infrastructure - Disaster Risk Management
Plan. Develop. Monitor.

Development Monitors is an interdisciplinary consulting company that designs and implements sustainable solutions across multiple fields and sectors. We leverage low-cost and open-source hardware and software that can be maintained by our local partners.

18 implementations · 6 countries · 5 institutional partners Scroll

A development engineering firm built around fieldwork.

Development Monitors is a US-registered company founded in 2017 by two experienced international research and development specialists, Dr. James Weeks and Mr. Umesh Tiwari.

Development Monitors is a development engineering company focused on tailoring and applying innovative technologies — including artificial intelligence and machine learning, geospatial asset risk management, autonomous drones and weather stations, and remote sensing and high-resolution aerial and satellite imagery — to solve research and development challenges across a wide range of fields and sectors.

Since 2018, the firm has partnered with The Washington Center to host over 70 undergraduate and graduate students majoring in computer science, engineering, and international relations from ten countries for three- to four-month full-time internships.

Team

Engineers · Social scientists · Health specialists · Developers
  • Dr. James Weeks Founder & President USA
  • Umesh Tiwari Co-Founder & Vice President India
  • Richard Ellert Senior Advisor, Water Sector Germany
  • David Hinkle Senior Advisor, Applied Technology USA
  • Alma Anaam Advisor, Data Science Yemen
  • Larry Weeks Senior Advisor, Infrastructure USA
  • Professor Robin White Advisor, Agriculture and Livestock USA
  • Professor Kevin Kochersberger Advisor, Drone Technologies USA

Capabilities span research, software, and field engineering.

Asset Register & Threat Mapping System

Decision support for resilient water systems.

ARTMS combines a georeferenced asset register, hazard overlays, water-quality evidence, and dashboard analytics so utilities can see where assets are, how they are performing, and which investments should come first.

ARTMS water supply system asset register
01 / Register

Build a verified asset inventory.

Import utility data and field observations for sources, intakes, pumping stations, mains, reservoirs, treatment plants, distribution pipelines, and other water supply components.

02 / Map

Connect assets to place.

Display every asset in an interactive map environment with OSM or satellite basemaps, administrative boundaries, utility layers, and project-specific geographies.

03 / Prioritize

Turn diagnostics into decisions.

Overlay landslide, flood, earthquake, and watershed risk layers, then rank assets by condition, criticality, and exposure to guide maintenance and resilience investments.

Dashboard concept

From desktop GIS to a utility-facing dashboard.

The dashboard concept brings the asset register, asset criticality level, map view, and water-quality table into a single utility-facing workspace. The updated Lekhnath view shows how field-verified infrastructure data, map-linked assets, maintenance priorities, and water-quality records can sit together for planning, monitoring, and financial planning.

LekhnathAsset registerMap windowAsset criticality levelWater quality
ARTMS Dashboard for Lekhnath showing asset register, map view, asset criticality level, and water quality panels
01

Asset register

Keep the verified register visible next to the map, with asset type, material, ward, installation year, and condition filters.

02

Map window

Make hazards work like interactive layers so landslide, flood, and other exposure data can be toggled against the selected asset.

03

Asset criticality level

Use the standard red, yellow, and green scheme to communicate high, medium, and low criticality assets at a glance.

04

Water quality

Compare standard values with tested values and flag compliant or non-compliant results for operational review.

Research Integrity in Global Open Review Agent

Rapid landscape assessment for research integrity.

RIGORA triages research landscapes for questionable research practices, combining structured user inputs, academic-source retrieval, evidence extraction, source curation, and expert review into an AI-assisted briefing workflow.

Purpose-built AI agent designed to support expert reviews of research landscapes, not replace them.

A1

Sufficiency validation

Checks whether the user supplied enough scope to run a useful review and asks follow-up questions when the prompt is incomplete.

A2

Search and curation

Generates targeted queries, retrieves sources, classifies relevance, and builds a curated source list for the next stage.

A3

Evidence extraction

Extracts report-tailored evidence from each source, with review screens for accepting, rejecting, or refining the extracted material.

A4

Structured memo

Generates a concise briefing memo from accepted evidence, with AI-generated labeling and explicit verification requirements.

A5

Expert review

Keeps domain experts in the loop for judgment calls, methodological interpretation, and final sign-off before dissemination.

ModelsSupports selectable model use across agents, including local Gemma workflows and cloud-hosted ChatGPT options when appropriate.
Search enginesDesigned around mixed source retrieval from Google Scholar, Crossref, Semantic Scholar, OpenAlex, and user-provided materials.
ReasoningUses structured reasoning, branch review, and retrieval-augmented evidence paths to make intermediate decisions inspectable.
ControlsSupports semi-automated operation with checkpoints for query approval, source selection, evidence review, and final memo review.

Example Questionable Research Practice lenses.

In crop science and agronomy testing, the platform can surface recurring methodological risk patterns for expert review.

  • Overgeneralization from narrow environment coverage
  • Opaque or misspecified analysis models
  • Weak replication and error control
  • Noncomparable pooling and design drift
  • Confounded or bundled treatment structures
  • Fragmented methods and incomplete outcomes
  • Selective filtering of problematic trials
Output / Structured Briefing Memo

From screened evidence to a review-ready briefing.

RIGORA is being developed to produce an assessment memo that summarizes the research landscape, anchors findings in selected sources, identifies Questionable Research Practice indicators,

FormatExecutive summary and main assessment
EvidenceSource-specific vignettes and methods flags
ReviewHuman validation before use

Engineering, ground-truthed.

A working archive of fieldwork - watersheds and water mains, asset registries, coastal baselines, analytical maps, and partner consultations captured on assignment from around the globe.

Workers installing water supply pipes in a mountain valley
F·01 ARTMS water supply system asset register
Forest stream with georeferenced field-capture overlay
F·02 Watershed asset registry · georeferenced field capture Surkhet · Nepal
Dry rocky riverbed in mountainous landscape
F·03 Wadi documentation for community-based disaster risk management CBDRM · Afghanistan
Workers in stone-walled construction excavation site
F·04 Construction sector field assessment · stone retaining works Sana'a · Yemen
Custom autonomous drone weighing 234 grams on a kitchen scale
F·05 234 g autonomous drone · Virginia Tech collaboration USA · Lab
Excavated trench with newly installed water main pipe
F·06 Water main installation · trenching Yemen
Pile of solid waste on a Yemeni street
F·07 Solid waste cycle assessment · Bani Bahlul Sana'a · Yemen
Four people in a meeting room with one giving a thumbs up
F·09 Partner consultation · field office Stakeholder engagement
3D-printed fixed-wing drones on a workshop table
F·103D-printed, fixed-wing drones for risk mappingDrone technology
Mapping and analytics
Watershed flood risk mapping in Aden, Yemen
M·01 Watershed flood risk mapping in Aden, Yemen Geospatial output
Automated building detection and flash flood risk analysis web map
M·02Automated building detection and flash flood risk analysis in Blacksburg, VirginiaGeospatial output

From the Hindu Kush to the Red Sea coast.

Implementation countries Interactive map · Six countries · Eighteen prime contracts

Counts reflect prime contracts. Cross-regional row covers Gates Foundation research projects spanning sub-Saharan Africa, India, and Nepal. Total: 18.

Peer-reviewed work in Remote Sensing.

Drone-Based Community Assessment paper
Research paper 30 April 2021

Drone-based Community Assessment, Planning, and Disaster Risk Management for Sustainable Development

doi.org/10.3390/rs13091739
Read paper
Post-Flood Analysis paper
Research paper 04 October 2022

Fast Flood Analysis for Damage and Restoration Assessment Using Drone Imagery

doi.org/10.3390/rs14194952
Read paper

Let's build something together.

Headquarters Arlington, Virginia, USA Satellite office Delhi, India Established 2017
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