Company Detail Table
SIM Provider Detail
Daily Data Table First 30 rows shown
Weekday/Weekend rates use the same normalization — denominator = present fleet size for accurate cross-period comparison.
Region Detail Table
Circle Table Top 25 shown
Scroll to zoom · Click a cluster to expand · Click a marker for meter details · Click a table row to fly to location
Location Table — click row to zoom map
Critical Alerts
Key Findings
Recommended Actions — Priority Order
| Rank | Priority | Area | Finding | Meters at Risk | Recommended Action | Expected Impact |
|---|
Each meter (MSN) is classified by how consistently it communicated across the full historical period.
Exact thresholds:
Always Present = 100% (communicated on every single active day) ·
Partial = strictly between 0% and 100% (even 99.1% counts as Partial) ·
Always Absent = 0% (never communicated on any active day).
All values computed dynamically from your uploaded file — no hardcoding.
Overall Fleet Distribution all historical MSNs · by attendance class
Monthly % Trend normalized to present fleet size · % of — meters
Month-wise Attendance Breakdown absolute meter counts · stacked · tooltip shows % of present fleet (denominator = —)
Always Absent Meters
Comm rate = 0% across all active days — require immediate field investigation · top 30 shown
| # | MSN / Meter ID | Overall Rate | Active Days | Days Communicated | Days Silent | Priority |
|---|
Partial / Inconsistent Meters
0% < rate < 100% · sorted worst-first · top 20 shown
| # | MSN / Meter ID | Overall Rate | Active Days | Days Communicated | Days Silent | Status |
|---|
For every Partial meter (comm rate strictly between 0% and 100%), the full
True/False/null sequence from Dailycommspast is analyzed in 8 steps to detect
a recognizable communication rhythm. Results update automatically with each uploaded file.
Sparklines show the last 60 active days —
communicated ·
did not communicate.
Pattern Distribution count of partial meters per detected pattern
Avg On-Run vs Avg Off-Run each dot = one meter · colored by pattern · clusters = similar rhythms
What Each Pattern Means
Partial Meter Detail
Sorted worst-rate first · top 50 shown · WD% = weekday comm rate · WE% = weekend comm rate
| # | MSN | Rate | Pattern | Avg On | Avg Off | Alt% | WD% | WE% | Trend | Last 60 Active Days → |
|---|
Individual Meter Lookup
Search any MSN from the active fleet. See its personal communication trend, attendance class, detected pattern (if partial), region, network, and weekday vs weekend breakdown — all derived from your uploaded file.
Search for a Meter
Upload your Excel file, then type any MSN in the box above.
You'll see that meter's full communication profile.
You'll see that meter's full communication profile.
What-If Scenario Controls ● LIVE
90%99%99%
−1 pp+0 pp+3 pp
13 months12
Comm Rate — History + Projection normalized to present fleet
Monthly Comm Rate History normalized · % of present fleet
Month-over-Month Change pp = percentage points
Monthly History Table Normalized — denominator = present fleet
| Month | Days | Comm Events | Avg Daily Comm % | MoM Change | vs SLA Target |
|---|
Pick any date range — even a single day. The dashboard shows you exactly what happened in that window: comm rate per day, dips, spikes, and smart diagnosis of every anomaly with possible root causes.
Can be 1 day or many. Every dip & spike gets diagnosed automatically.
QUICK:
Profile Data — Each meter sends three types of profiles:
BLP (Block Load Profile — 30-min energy blocks, up to 1,128 records/meter),
DLP (Daily Load Profile — 24 daily summaries/meter),
Push IP (Push IP Profile — event-driven pushes, up to 2,103 records/meter).
Data sourced from the Profile Data sheet.
BLP — Record Count Distribution Block Load Profile
DLP — Record Count Distribution Daily Load Profile
Push IP — Record Count Distribution Push IP Profile
Fleet Coverage — Meters per Profile Type meters reporting vs present fleet
Average Records per Meter mean count across reporting meters
Top Meters — Highest Record Counts per Profile Type Top 20 per profile · sorted descending
BLP — Top 20
| # | MSN | BLP Count | vs Max |
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DLP — Top 20
| # | MSN | DLP Count | vs Max |
|---|
Push IP — Top 20
| # | MSN | Push IP Count | vs Max |
|---|
Low-Activity Meters — Bottom 20 per Profile Type Meters with fewest records — may need investigation
BLP — Bottom 20
| # | MSN | BLP Count | vs Max |
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DLP — Bottom 20
| # | MSN | DLP Count | vs Max |
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Push IP — Bottom 20
| # | MSN | Push IP Count | vs Max |
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Billing Analytics — Classifies each meter's billing record from the Billingdata sheet.
A billing_timestamp at exactly 00:00:00 = Automatic Billing.
Any other time = Manual Billing.
Meters with both types across records are flagged as Mixed.
Billing Type Split Automatic vs Manual records
Daily Billing Volume Auto & Manual per date
Manual Billing — Hour Distribution When manual reads occur
Meter Classification Auto-only · Manual-only · Mixed
Manual & Mixed Meters MSNs with at least one manual billing record
| # | MSN | Auto Records | Manual Records | Classification | Manual Times |
|---|
Root Cause Analyzer
— Type any MSN to diagnose why it is failing, non-communicating, or billing manually
Analyzes: communication status · failure timeline · SIM/company context · billing type · month-over-month pattern · fleet peer comparison
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Dashboard AI
Ask about your data
Welcome! I can help you understand your smart meter data. Try asking about meter counts, communication rates, networks, or companies.