Farm Dashboard

Monitor your investments, track crop health, and view projected returns.

๐Ÿ‡ฒ๐Ÿ‡พ

Kedah

Rice Bowl of Malaysia

Agricultural Profile

Accounts for ~50% of Malaysia total rice production

Arable land High โ€” flat alluvial plains
Key crops Rice (Paddy), Harum Manis Mango, Red Bird's Eye Chili, Watermelon

Logistics to Singapore

Method Cross-border road freight (dry/reefer trucks)
Transit time 1โ€“3 days

North-South Expressway (NSE, ~800+ km) โ†’ Johor Bahru / Woodlands / Tuas Checkpoints

Export Crops to Singapore

Red Bird's Eye Chili (Cili Padi)

Vegetables

SGD 4.50 - 7.00/

Harum Manis / Chokanan Mango

Fruits

SGD 3.00 - 5.50/

Cost Breakdown

Red Bird's Eye Chili (Cili Padi) | Kedah | 1 acre

Lease (annual) SGD 575
Seed / Seedling SGD 110
Inputs (fertilizer, pesticide, irrigation) SGD 650
Contract Labor SGD 800
Storage & packhouse SGD 155
Local transport + commission SGD 235
Farm machinery rental SGD 175
Export logistics to Singapore SGD 475
Total Cost SGD 3,175

ROI Analysis

Red Bird's Eye Chili (Cili Padi) exported to Singapore from Kedah

Total Investment

SGD 3,175

Projected Wholesale Revenue

SGD 20,125

Net Profit

SGD 16,950

Return on Investment

534%

Lifecycle 3 months
Crop Analytics

Real-time field intelligence

Monitor every metric across your plots โ€” yield, health, water usage, pest activity, and growth rates โ€” all updated live from field sensors and satellite feeds.

12,480 kg
Total Yield
+14.2%
94.6%
Health Index
+2.1%
87.3%
Water Efficiency
+5.8%
2 Active
Pest Alerts
-3
42%
Soil Moisture
+1.5%
3.2 cm/day
Growth Rate
+0.4

Weekly Yield

kg harvested per day this week

Mon
Tue
Wed
Thu
Fri
Sat
Sun

Crop Health by Variety

AI-derived health scores per crop type

Millets 96%
Tomatoes 88%
Chili 91%
Spinach 72%
Papaya 83%
Auto Pollination

Self-recharging drone fleet

Autonomous pollination drones that monitor battery levels, return to solar charging stations, and redeploy โ€” operating 24/7 without human intervention.

Solar Self-Recharge

Drones autonomously return to solar-powered docking stations when below 20% โ€” no manual intervention.

Precision Pollination

Flight paths optimized per crop type with micro-nozzle pollen dispersal for maximum fruit set.

Swarm Coordination

Multiple drones coordinate coverage zones in real-time โ€” no overlap, no missed rows.

Night Operation

Infrared navigation enables pollination during optimal nocturnal windows for certain crops.

Fleet Status

6 drones deployed across 4 plots

4 Active 1 Charging 1 Idle
DRN-001 active

Pollinating millet rows 1-24

Location Kedah Plot A
Battery 78%
Area covered 1.2 ha
DRN-002 active

Pollinating tomato rows 8-16

Location Kedah Plot B
Battery 62%
Area covered 0.9 ha
DRN-003 recharging

Solar recharging โ€” ETA 18 min

Location Base Station
Battery 34%
Area covered 1.5 ha
DRN-004 active

Pollinating strawberry rows 1-12

Location Cameron Terrace
Battery 91%
Area covered 0.6 ha
DRN-005 active

Pollinating chili rows 4-20

Location Java West Plot
Battery 55%
Area covered 2.1 ha
DRN-006 idle

Awaiting dispatch

Location Base Station
Battery 100%
Area covered 0 ha
Yield Forecasting

Computer vision stress scouting

AI-powered cameras scan every row for disease, nutrient deficiency, water stress, and pest damage โ€” predicting yield outcomes before harvest.

Live Stress Alerts

critical Disease
12 min ago

Kedah Plot A Row 12

Early blight detected on tomato leaves โ€” irregular brown lesions with concentric rings.

CV Confidence 94.2%
warning Nutrient Deficiency
34 min ago

Perlis Highland Row 8

Chlorosis pattern on lower millet leaves โ€” likely nitrogen deficiency.

CV Confidence 87.6%
warning Water Stress
1 hr ago

Java West Plot Chili

Leaf curling and wilting detected โ€” irrigation schedule adjustment recommended.

CV Confidence 91.3%
info Growth Stage
2 hr ago

Cameron Terrace Row 4

Strawberry plants entering flowering stage โ€” pollination drone dispatch recommended.

CV Confidence 96.8%

Yield Predictions

Finger Millet 34d to harvest
Current

3,200 kg

Predicted

4,800 kg

Prediction confidence 92%
Tomato 21d to harvest
Current

1,800 kg

Predicted

2,600 kg

Prediction confidence 88%
Chili 45d to harvest
Current

900 kg

Predicted

1,400 kg

Prediction confidence 85%
Baby Spinach 12d to harvest
Current

600 kg

Predicted

720 kg

Prediction confidence 94%

How Computer Vision Scouting Works

High-resolution field cameras capture leaf-level imagery every 15 minutes. A trained CV model analyzes color, texture, and shape patterns to detect disease, nutrient deficiency, water stress, and pest damage โ€” triggering alerts before visible symptoms reach human detection thresholds.

Labor Monitoring

Secured IP camera field view

Monitor daily labor activity on every field through encrypted IP cameras โ€” with real-time worker tracking, motion detection, and tamper-proof audit logs.

End-to-End Encryption

AES-256 at rest, TLS 1.3 in transit โ€” zero plain-text exposure.

Role-Based Access

Field managers, auditors, and owners each get different view permissions.

Tamper-Proof Logs

All camera events are hashed and time-stamped on an immutable audit trail.

On-Premise Option

Run the entire camera stack locally โ€” no cloud dependency required.

Camera Fleet

CAM-001
recording

North Field Gate

Kedah Plot A

Workers detected 3
Last motion 2 min ago
Encryption AES-256 + TLS 1.3
CAM-002
recording

Main Processing Area

Kedah Storage

Workers detected 5
Last motion Live
Encryption AES-256 + TLS 1.3
CAM-003
recording

South Paddy Fields

Kedah Plot B

Workers detected 2
Last motion 8 min ago
Encryption AES-256 + TLS 1.3
CAM-004
online

Cameron Terrace View

Cameron Highlands

Workers detected 0
Last motion 1 hr ago
Encryption AES-256 + TLS 1.3
CAM-005
recording

Java Processing Hub

West Java

Workers detected 8
Last motion Live
Encryption AES-256 + TLS 1.3
CAM-006
offline

Bali Organic Terrace

Bali

Workers detected 0
Last motion 3 days ago
Encryption AES-256 + TLS 1.3

Today's Activity Log

06:00

Field crew arrived โ€” 4 workers checked in at North Field Gate

07:30

Harvesting began on millet rows 1-12 โ€” 3 workers active

10:15

Break time โ€” all workers returned to processing area

10:45

Afternoon shift started โ€” 2 workers deployed to pest scouting

13:00

Quality inspection โ€” supervisor verified 240 kg batch

15:30

Field maintenance โ€” irrigation line repair on row 8

Daily Summary
18
Total workers
9h 24m
Total logged hours
5 / 6
Cameras online
EOF