Website Portfolio Copy — Cold-Chain Traceability, Directed Picking, FIFO Enforcement & IoT Monitoring
Project positioning
Seencode was developed as a cyber-physical warehouse execution and cold-storage traceability system for a pilot deployment at Samen al-Aemeh Cold Storage in Mashhad.
The project combined physical warehouse redesign with software control:
- barcode-based location addressing,
- pallet identification,
- carton-level identification,
- Jet Printer barcode generation,
- forklift-directed picking through a tablet interface,
- FIFO-oriented stock selection,
- real-time warehouse control through a web application,
- Raspberry Pi / DHT22 environmental monitoring,
- reporting over existing cold-storage chip data,
- and a proposed QR-based consumer traceability extension.
The core operational problem was not merely inventory recording. It was enforcing the correct physical movement of stock inside a very cold environment where forklift operators could otherwise prefer the nearest accessible pallets instead of traveling deeper into the cold store to retrieve the oldest stock.
Seencode therefore acted as an execution system:
it told the operator what to move, from where, and in what order.
Classification
- Project Type: Warehouse Execution System / Cold-Chain Traceability / IoT
- Project Name: Seencode
- Deployment Type: Pilot implementation
- Pilot Site: Samen al-Aemeh Cold Storage, Mashhad
- Domain: Cold Storage / Meat & Meat Products / Warehouse Operations
- Facility Scale: 16 storage halls / cold-storage sections
- Core Workflow: Barcode-driven inbound, storage, retrieval and outbound control
- Operator Interface: Tablet-based forklift guidance
- Location Model: Barcoded floor-grid positions
- Asset Identification: Carton + pallet + physical location
- Printing: Jet Printer barcode printing
- Environmental Monitoring: Raspberry Pi + DHT22
- Web Layer: Seencode web application
- Inventory Logic: Oldest-stock-directed retrieval / FIFO enforcement
- Reporting: Filterable storage-condition and location reports
- Future Extension: QR traceability for end consumers
- Portfolio Relevance: Very High
- Suggested CV Relevance: Tier A/B — Strong Architecture & Industrial Digitalization Evidence
Website Card
Title:
Seencode — Cold Storage & Warehouse Execution System
One-line Description:
A barcode-driven cold-storage execution platform that synchronized cartons, pallets, floor locations, forklift operators, environmental sensors, and a web control system to enforce oldest-stock retrieval and reduce operational loss.
Categories:
- Warehouse Execution
- Cold Chain
- Traceability
- Barcode Systems
- IoT
- Raspberry Pi
- Web Applications
- Industrial Digitalization
- Logistics
- Inventory Control
- Cyber-Physical Systems
Technology / Concept Tags:Raspberry Pi · DHT22 · Barcode · Jet Printer · Tablet UI · Web Application · FIFO · Warehouse Location Addressing · Directed Picking · Cold Storage · Traceability
Executive Summary
Seencode was built to solve a physical warehouse-control problem in cold storage.
The existing operation stored meat and meat products across multiple cold rooms.
In principle, older stock should leave before newer stock.
In practice, the extreme cold created a human-behavior problem:
a forklift operator could repeatedly select the easiest and closest pallet near the front of the cold room, while older stock deeper inside remained untouched.
This could lead to:
- aging stock,
- hidden inventory,
- shrinkage,
- incorrect rotation,
- location uncertainty,
- operational inefficiency.
Seencode replaced manual memory and operator convenience with a digitally directed workflow.
The system knew:
WHAT
is stored
ON WHICH PALLET
AT WHICH EXACT FLOOR LOCATION
IN WHICH STORAGE AREA
AND WHICH STOCK IS OLDEST
When stock needed to leave, the system identified the oldest eligible inventory and instructed the forklift operator through a tablet:
go to this exact location and retrieve this exact pallet.
Core Business Problem
The project addressed several linked operational problems.
1. Cold-Environment Human Behavior
Cold rooms are uncomfortable working environments.
A forklift operator naturally has an incentive to minimize time spent deep inside the refrigerated area.
Without digital control, this can create a pattern:
Nearest pallet
↓
Picked first
↓
Newer stock leaves
Older pallet
↓
Remains deeper inside
↓
Aging / hidden stock
The resulting process may appear organized on paper while failing operationally.
2. Weak Physical Location Awareness
If stock is tracked only by product or pallet, the system still does not know exactly where it sits.
Seencode introduced a physical addressing model.
3. Manual Stock Rotation
FIFO rules are only useful if they are actively enforced.
Seencode converted FIFO from a policy into an operational instruction.
4. Traceability
The system linked:
- carton,
- pallet,
- storage location,
- movement,
- environmental conditions.
This created a stronger digital record of the cold-chain process.
High-Level Architecture
SEENCODE
│
┌───────────────┼────────────────┐
│ │ │
▼ ▼ ▼
Carton Barcode Pallet Barcode Location Barcode
│ │ │
└───────────────┼────────────────┘
↓
Web Application
↓
Warehouse State Model
↓
Oldest Eligible Stock Engine
↓
Forklift Tablet UI
↓
Directed Physical Picking
In parallel:
DHT22
↓
Raspberry Pi
↓
Environmental Data
↓
Seencode Web Application
↓
Monitoring / Reporting
Physical Warehouse Digitization
One of the strongest aspects of Seencode was that the warehouse itself was converted into a machine-addressable space.
This was not only a software project.
The physical environment was modified to match the software model.
Step 1 — Carton Identification
A Jet Printer was installed to print:
- identifiers,
- barcodes,
onto cartons / meat boxes.
This created a digital identity for physical stock.
Conceptually:
Incoming Carton
↓
Unique ID
↓
Barcode
↓
Printed on Carton
Step 2 — Barcoded Floor Grid
The cold-storage floor was physically divided into a grid.
Each floor position received a barcode.
The result was a location-addressing layer:
Hall
↓
Grid Position
↓
Location Barcode
A floor position therefore became a digital warehouse address.
This is one of the core architectural ideas of Seencode.
Step 3 — Pallet Identification
The large metal pallets / racks placed on those positions were also barcoded.
The digital model could therefore represent:
Carton
↓
Pallet
↓
Floor Position
↓
Cold-Storage Hall
This gave the software enough context to resolve a physical location.
Three-Level Identification Model
Seencode effectively maintained three physical identity layers:
Level 1 — Carton
The individual box / meat package.
Level 2 — Pallet
The handling unit used by the forklift.
Level 3 — Location
The physical warehouse position.
Together:
Carton ID
↓
Pallet ID
↓
Location ID
This is the foundation of traceable warehouse execution.
Inbound Workflow
A conceptual inbound flow:
Carton Arrives
↓
Barcode Printed
↓
Carton Assigned to Pallet
↓
Pallet Identified
↓
Storage Position Selected
↓
Floor Position Identified
↓
System Records Location
At the end of the process, the system could answer:
Where is this carton?
and:
What stock is currently at this location?
Warehouse Location Model
A useful conceptual hierarchy:
Facility
↓
Hall
↓
Grid Position
↓
Pallet
↓
Cartons
This allows movement to be represented digitally.
Example:
Hall 05
Position C-14
Pallet P-0028
Cartons:
C-104411
C-104412
C-104413
Forklift Tablet Interface
The forklift operator received a tablet.
This was critical because Seencode did not rely on the operator remembering stock locations.
The application told the operator where to go.
Example:
OUTBOUND TASK
Product:
Beef / Batch X
Required:
20 cartons
Oldest eligible stock:
Hall: 07
Location: C-14
Pallet: P-028
ACTION:
Retrieve pallet
This changed the worker interaction model from:
operator decides
to:
system directs
Directed Picking
This is one of the strongest technical/product concepts in the project.
The system calculated the correct stock to retrieve and gave the operator a physical destination.
Conceptually:
Outbound Request
↓
Find Eligible Inventory
↓
Sort by Entry Age
↓
Select Oldest Stock
↓
Resolve Physical Location
↓
Generate Forklift Task
↓
Tablet Instruction
↓
Scan / Confirm
This is essentially system-directed warehouse picking.
FIFO Enforcement
The operational objective was to retrieve the oldest eligible stock first.
The system therefore enforced a FIFO-style rotation.
First In
↓
Oldest Available Stock
↓
First Out
The key improvement was not the existence of FIFO as a concept.
It was enforcement.
Before Seencode:
Operator Convenience
>
Warehouse Rotation Rule
After Seencode:
System Instruction
>
Operator Guesswork
Why This Matters
Without directed picking, a cold-storage worker may reasonably choose the easiest pallet to reach.
That behavior is understandable but creates a structural risk.
Seencode used digital instructions to reduce that ambiguity.
This is a strong example of software changing physical operational behavior.
Web Control Application
The web application acted as the control plane.
It was responsible for coordinating:
- stock,
- physical locations,
- pallet assignments,
- movements,
- retrieval logic,
- monitoring,
- reporting.
The web system was not only a dashboard.
It represented the current digital state of the warehouse.
Operator Workflow
A simplified execution sequence:
Warehouse Request
↓
Seencode
↓
Task Created
↓
Tablet
↓
Forklift Operator
↓
Location
↓
Pallet
↓
Confirmation
↓
Inventory State Updated
Facility Scale
The pilot site contained approximately 16 cold-storage halls / sections.
That scale matters because location addressing becomes increasingly valuable as the number of possible physical storage positions grows.
A manual memory-based approach becomes less reliable as:
- halls increase,
- pallets increase,
- product diversity grows,
- movements increase.
Environmental Monitoring
The project also extended the Raspberry Pi monitoring model used in the earlier poultry-farm project.
For the cold-storage cooling environment, DHT22 sensors were used.
The monitoring layer captured:
- temperature,
- humidity.
The data could be incorporated into the web application.
Environmental Architecture
DHT22
↓
Raspberry Pi
↓
Network
↓
Seencode Backend
↓
Storage Condition Monitoring
↓
Reports
This linked warehouse operations and environmental conditions inside one control system.
Development Phase 1 — Physical Barcode Execution
The first major implementation phase focused on physical warehouse control.
This included:
- Jet Printer identification,
- carton barcodes,
- pallet barcodes,
- floor-grid barcodes,
- warehouse location mapping,
- forklift guidance,
- directed picking.
This phase created the operational core.
Development Phase 2 — Monitoring & Reporting
The second phase expanded the system with data from existing cold-storage chips / monitoring systems.
The goal was to produce filterable reports covering:
- storage position,
- conditions,
- warehouse state,
- historical monitoring data.
Conceptually:
Existing Sensor / Chip Data
↓
Data Collection
↓
Seencode
↓
Filterable Reports
↓
Operational Control
Development Phase 3 — Consumer Traceability Proposal
The third development idea extended traceability beyond the cold store.
A proposal was made to reprint outgoing package information through a Jet Printer as a QR code.
The QR code could expose product-history information to the final consumer.
Proposed information included:
- storage method,
- slaughter date/time,
- slaughter location,
- product traceability details.
Conceptually:
Cold-Storage Record
↓
Outbound Package
↓
QR Code
↓
Consumer Scan
↓
Product History
This was a forward-looking traceability concept.
Cold-Chain Traceability Model
The project could represent traceability across multiple layers:
Product
↓
Carton
↓
Pallet
↓
Location
↓
Storage Conditions
↓
Outbound Movement
The proposed QR extension added:
Consumer
↓
Product History
Physical / Digital Synchronization
Seencode is best described as a cyber-physical system.
The software state had to match real warehouse state.
For example:
Digital:
Pallet P-028 is at C-14
Physical:
Pallet P-028 must actually be at C-14
If the two states diverge, the warehouse model becomes unreliable.
This makes scanning and task confirmation important.
Why Barcode Everywhere?
The system used barcodes on:
- floor locations,
- pallets,
- cartons.
This may look repetitive, but each barcode solved a different identity problem.
Floor Barcode
= WHERE
Pallet Barcode
= HANDLING UNIT
Carton Barcode
= WHAT
Together they form:
WHAT
ON WHAT
WHERE
Jet Printer Integration
Jet printing was particularly suitable for operational identification because it allowed identifiers to be applied directly to physical packaging.
The printer could support:
- carton identification,
- barcode generation,
- outgoing traceability information,
- later QR-code concepts.
Operator Verification
A robust execution flow can include scanning during each transition.
Example:
Instruction:
Go to C-14
Operator arrives
↓
Scan location barcode
↓
Scan pallet barcode
↓
System verifies
↓
Pick confirmed
This prevents the operator from accidentally taking stock from the wrong location.
Error Reduction
The system was intended to reduce errors such as:
- wrong pallet selection,
- incorrect location records,
- forgotten old stock,
- manual identification mistakes,
- inbound/outbound mismatch,
- hidden shrinkage.
Loss & Shrinkage Control
One of the project goals was reducing:
- shortage,
- loss,
- unexplained discrepancy,
- stock aging.
A traceable movement history helps explain:
what entered,
where it was stored,
when it moved,
what left.
Expiration Awareness
The system was also intended to improve control over storage time and product validity.
A stronger future version can distinguish:
- FIFO,
- FEFO,
- lot expiry,
- quarantine,
- blocked stock.
Historical FIFO Note
The historical objective was to ensure that older stock was retrieved before newer stock.
For public documentation, the project should describe this as:
oldest-stock-directed retrieval / FIFO enforcement
unless recovered source or documentation shows that expiry date rather than entry date was the primary sorting criterion.
If expiry date was the controlling factor, the more precise term would be FEFO.
My Role
My role covered both software and physical-system implementation.
Responsibilities included:
- understanding cold-storage operational problems,
- designing the barcode model,
- defining location addressing,
- creating the web application,
- implementing warehouse-control logic,
- implementing oldest-stock selection,
- building the forklift tablet workflow,
- integrating carton/pallet/location identities,
- preparing barcode generation,
- working with Jet Printer output,
- implementing Raspberry Pi monitoring,
- integrating DHT22 sensors,
- incorporating storage-condition reporting,
- designing the pilot workflow,
- testing the system in the facility,
- and designing the proposed QR-based consumer traceability extension.
What Makes Seencode Different from a Normal Inventory System
A conventional inventory application may know:
200 cartons of Product X exist.
Seencode needed to know:
Which cartons?
On which pallet?
At which physical grid position?
Inside which hall?
How old are they?
Which one should leave next?
That is a much richer operational model.
Warehouse Management vs Warehouse Execution
The strongest way to position Seencode is not only as a WMS.
It also contains WES-like behavior.
Management
- inventory state,
- reporting,
- tracking.
Execution
- selects stock,
- resolves location,
- directs forklift operator,
- controls movement order.
This execution layer is the heart of the project.
Cyber-Physical System Perspective
Seencode connected software state to physical reality.
Web Application
↕
Tablet
↕
Forklift Operator
↕
Pallet
↕
Physical Location
In parallel:
Environment
↓
DHT22
↓
Raspberry Pi
↓
Monitoring
That makes the project a strong example of industrial digitalization.
Outcome
The pilot was physically implemented.
The warehouse environment was modified with barcode-addressable positions.
Pallets and cartons were integrated into the identification model.
The software directed warehouse operations and provided digital control over movements.
Later expansion encountered funding/organizational difficulties associated with the institutional environment.
The portfolio should avoid characterizing those later circumstances as proven fraud unless independently documented.
Recommended wording:
The pilot implementation was completed successfully, but broader continuation was limited by funding and institutional constraints after the project moved into a larger organizational environment.
This keeps the public portfolio factual and defensible.
Evidence Available
Current evidence includes:
- photographs of the barcoded cold-storage floor,
- barcode image files,
- photographs of the cold-storage halls,
- photographs of metal pallet/rack infrastructure,
- packaging / pallet evidence,
- historical project description,
- physical deployment evidence.
Potential additional evidence may include:
- original web application,
- database,
- tablet UI,
- barcode generator,
- Jet Printer configuration,
- sensor code,
- monitoring reports,
- video of the pilot system.
Evidence Status
Recommended label:
Strongly Partially Verified — Physical deployment photographs document barcoded warehouse locations and infrastructure; the project page should add the original web application, tablet workflow, and source artifacts where available.
Engineering Value
This project demonstrates multiple architecture layers at once.
Identification
+
Location Modeling
+
Inventory
+
Execution Logic
+
Operator UX
+
IoT
+
Reporting
+
Traceability
That makes Seencode significantly stronger than a conventional CRUD business system.
Career Evidence
Seencode demonstrates:
- Warehouse Execution Systems
- Industrial Digitalization
- Barcode Architecture
- Physical Location Modeling
- Directed Picking
- FIFO Enforcement
- Traceability
- Inventory Architecture
- Tablet Workflow Design
- Raspberry Pi / IoT
- Cold-Chain Monitoring
- Cyber-Physical Systems
- End-to-End Architecture
- Operational Process Design
- Product Engineering
CV Relevance
Tier A/B — Major Portfolio Project
This project can support senior engineering / architecture discussions because it demonstrates the ability to design beyond software screens.
It crosses:
Physical Facility
→ Sensors
→ Barcodes
→ Workers
→ Mobile Interface
→ Backend
→ Business Rules
→ Traceability
This is particularly relevant to:
- Solution Architecture
- Industrial Software
- Logistics
- Warehouse Systems
- IoT
- Digital Transformation
- Backend Architecture
- Operations Technology
Interview Story
Situation
A large refrigerated storage facility in Mashhad handled meat and meat products across multiple cold-storage halls.
The operational problem was that workers could physically choose the most accessible pallets rather than the oldest stock, especially because moving deeper into extremely cold rooms was uncomfortable.
Task
The system needed to digitize physical warehouse positions, track cartons and pallets, and actively guide forklift operators to the correct stock location.
Action
I designed a barcode-based physical addressing model for the warehouse, marked floor locations, barcoded pallets and cartons, integrated Jet Printer identification, built the Seencode web application, and gave forklift operators a tablet interface that directed them to the exact location of the oldest eligible stock.
I also integrated Raspberry Pi/DHT22 environmental monitoring and later expanded reporting using existing cold-storage monitoring data.
Result
The pilot converted warehouse rotation from a manually interpreted policy into a digitally directed workflow.
The system could identify the oldest stock, locate it physically, direct the operator to the correct position, and maintain a stronger traceability record across the facility.
Suggested Website Full Description
Overview
Seencode was a barcode-driven warehouse execution and cold-storage traceability system piloted at Samen al-Aemeh Cold Storage in Mashhad.
The project connected physical warehouse locations, pallets, cartons, forklift operators, environmental sensors, and a web application into one operational model.
The Challenge
The facility handled meat products in very cold storage halls.
Although older inventory should be selected first, manual work created a practical problem:
operators could repeatedly choose the easiest pallet near the front instead of entering deeper into the cold room to retrieve older stock.
That created a gap between warehouse policy and warehouse reality.
Original Solution
Seencode converted the warehouse into a barcode-addressable environment.
- floor positions were barcoded,
- metal pallets were barcoded,
- cartons received barcodes through a Jet Printer,
- the web application maintained the relationship between stock and location,
- forklift operators received instructions through tablets.
When stock needed to leave, the application selected the oldest eligible inventory and told the operator exactly where to retrieve it.
Environmental Monitoring
DHT22 sensors and Raspberry Pi devices were used to monitor temperature and humidity in the cold-storage environment.
The monitoring data became part of the wider control/reporting solution.
Later Development
The project later expanded toward:
- reports using existing cold-storage chip data,
- richer filtering,
- storage-condition analysis,
- a proposed consumer-facing QR traceability system for outgoing products.
V2 — Modern Seencode Platform
The modern reconstruction can evolve Seencode into a complete cold-chain Warehouse Execution and Traceability Platform.
Recommended V2 title:
Seencode — Cold-Chain Warehouse Execution Platform
V2 Architecture
Operator Apps
/ \
Forklift Tablet Admin Web
\ /
\ /
Seencode API
↓
Warehouse Execution Engine
┌────────────┼────────────┐
▼ ▼ ▼
Inventory Locations Tasks
│ │ │
└────────────┼────────────┘
↓
PostgreSQL
│
┌─────────────┼─────────────┐
▼ ▼ ▼
Redis IoT/MQTT Reporting
V2 Core Domain Model
Facility
Facility
↓
Zone
↓
Hall
↓
Location
Inventory
Product
↓
Lot
↓
Carton
↓
Pallet
Execution
Task
↓
Source Location
↓
Target Location
↓
Operator
↓
Confirmation
V2 Location Model
Each physical location should have:
- unique location ID,
- facility,
- hall,
- row,
- column,
- level,
- barcode / QR code,
- capacity,
- status.
V2 Inventory State
Each stock unit can preserve:
- product,
- lot,
- production date,
- slaughter date,
- expiry date,
- inbound date,
- pallet,
- current location,
- status.
FIFO / FEFO Engine
A modern implementation should support configurable retrieval policies.
Examples:
- FIFO
- FEFO
- lot priority
- customer-specific allocation
- quarantine rules
- blocked inventory
Directed Picking Engine
Order / Request
↓
Allocation Engine
↓
Eligible Inventory
↓
Rotation Policy
↓
Best Pick Candidate
↓
Location Resolution
↓
Forklift Task
Tablet UX
The operator screen should remain intentionally simple.
Example:
TASK #10422
Go to:
Hall 07
Location:
C-14
Pallet:
P-028
Product:
Beef Lot 2204
Quantity:
20
[Scan Location]
[Scan Pallet]
[Confirm]
The worker should not need to understand the database model.
Scan Validation
The system should verify:
- correct location,
- correct pallet,
- correct stock.
Wrong scan:
Expected P-028
Scanned P-031
STOP
Movement Ledger
Every physical movement should create an immutable event.
Example:
Pallet P-028
FROM C-14
TO Shipping-03
BY Operator 27
AT 14:32:11
This creates a traceable operational history.
Event-Sourced Possibility
For high auditability, warehouse movement can be represented as append-only events.
Received
Stored
Moved
Picked
Loaded
Shipped
The current inventory state can be derived from the movement history.
IoT V2
A modern cold-chain deployment can monitor:
- temperature,
- humidity,
- door status,
- refrigeration status,
- power failure,
- compressor state.
MQTT can provide telemetry.
Cold-Chain Alerts
Examples:
Temperature outside range
Door open too long
Sensor offline
Refrigeration fault
Alerts should be tied to the affected zone/hall.
Device Heartbeat
The platform should know whether a sensor is actually online.
No heartbeat
↓
Device Offline Alert
Historical Reporting
Modern reports can correlate:
- product history,
- physical location,
- storage duration,
- temperature history.
This improves traceability.
Consumer QR Traceability
The earlier project idea can become a modern public traceability endpoint.
Example QR page:
Product
Lot
Slaughter Date
Slaughter Location
Storage Facility
Storage Conditions
Dispatch Date
Only data approved for public disclosure should be exposed.
Security
A production system should include:
- RBAC,
- authenticated devices,
- signed APIs,
- TLS,
- audit logs,
- per-device credentials,
- backup strategy,
- secure tablet sessions.
Roles
Possible roles:
- Administrator
- Warehouse Manager
- Forklift Operator
- Quality Control
- Auditor
- Read-Only
Audit Trail
Critical actions include:
- location change,
- stock adjustment,
- manual allocation override,
- alert acknowledgement,
- threshold changes,
- user changes.
Offline Tablet Support
Cold-storage connectivity may be inconsistent.
The tablet client should support:
- cached current task,
- local scan validation where possible,
- queued confirmations,
- synchronization after reconnect.
Reliability
A warehouse execution system must fail safely.
Examples:
- duplicate scan protection,
- idempotent APIs,
- transaction boundaries,
- task locking,
- concurrent pick protection.
Concurrency Control
Two operators should not receive the same pallet simultaneously.
Example:
Pallet P-028
Allocated to Task A
↓
Locked
↓
Unavailable to Task B
Automated Testing
Domain Tests
- FIFO allocation
- FEFO allocation
- pallet assignment
- location capacity
- movement rules
Workflow Tests
- inbound
- put-away
- relocation
- picking
- shipping
Validation Tests
- wrong location scan
- wrong pallet scan
- duplicate pick
- concurrent allocation
Observability
Metrics could include:
- picks/hour,
- average travel time,
- task completion time,
- inventory age,
- location occupancy,
- sensor uptime,
- cold-chain alerts.
Operational Analytics
Seencode V2 can answer:
- Which halls contain aging stock?
- Which pallets are repeatedly relocated?
- Which operators have the longest pick routes?
- Which locations cause bottlenecks?
- What inventory is approaching expiry?
Optimization Opportunities
Future optimization could include:
- travel-distance optimization,
- slotting recommendations,
- dynamic put-away,
- route sequencing,
- forklift workload balancing.
Why Seencode Matters
Seencode is not important because it used barcodes.
Barcodes are simple.
The architecture is important because the system connected:
IDENTITY
+
LOCATION
+
TIME
+
WORKER
+
MOVEMENT
+
ENVIRONMENT
into one operational model.
That is what made the software capable of controlling a real warehouse workflow.
Short Website Card Copy
Seencode — Cold Storage & Warehouse Execution System
A barcode-driven warehouse execution platform that linked cartons, pallets, floor locations, forklift tablets, and IoT monitoring to enforce oldest-stock retrieval inside a 16-hall cold-storage facility.
Alternative One-Liners
Architecture-oriented
Designed a cyber-physical warehouse execution system linking barcode-addressed locations, pallet/carton identity, directed forklift picking, and environmental monitoring.
Operations-oriented
Digitized cold-storage movement by directing forklift operators to the exact location of the oldest eligible stock rather than relying on manual selection.
Traceability-oriented
Built a three-level traceability model connecting carton, pallet, and physical warehouse location with movement and environmental data.
Industrial IoT-oriented
Combined Raspberry Pi/DHT22 monitoring with barcode-driven warehouse execution and a web-based control platform.
Suggested Website Slug
/projects/seencode-cold-storage-warehouse-execution
Alternative:
/software/seencode-cold-chain-traceability
Cover Direction
Title
Seencode
Subtitle
Cold Storage & Warehouse Execution System
Supporting Line
Barcode Traceability · Directed Picking · FIFO · IoT Monitoring
Visual Direction
A premium square industrial software cover showing:
- cold-storage warehouse aisles,
- barcoded floor grid,
- forklift operator with tablet,
- metal pallet with barcode,
- cartons with barcode labels,
- web dashboard,
- Raspberry Pi / DHT22 environmental monitoring,
- digital arrows leading the operator to a highlighted warehouse location.
The visual should immediately communicate:
BARCODED WAREHOUSE
+
FORKLIFT
+
TABLET GUIDANCE
+
COLD STORAGE
+
DIGITAL CONTROL
This cover should look like an industrial logistics system, not generic inventory software.
Evidence Gallery Recommendation
Physical Deployment
- barcoded floor photographs,
- pallet / rack photographs,
- warehouse aisle photographs,
- carton barcode examples,
- Jet Printer output.
Software
If recovered:
- Seencode dashboard,
- forklift tablet UI,
- picking instruction screen,
- warehouse map,
- location database,
- reports.
Monitoring
- DHT22/Raspberry Pi setup,
- environmental dashboard,
- condition report.
V2
- architecture diagram,
- directed-picking workflow,
- QR consumer traceability,
- test suite,
- movement ledger.
Final Portfolio Statement
The central challenge in Seencode was not storing inventory data.
It was controlling real physical behavior inside a warehouse.
Before the system, the easiest pallet to reach could become the pallet most likely to leave.
Seencode changed that logic.
The system identified the oldest eligible stock, resolved its exact physical location, and directed the forklift operator to retrieve it.
The complete model was:
Carton
↓
Pallet
↓
Location
↓
Age / Rotation Rule
↓
Directed Task
↓
Forklift Operator
↓
Confirmed Movement
Combined with environmental monitoring and later traceability extensions, Seencode became a true bridge between software and physical logistics.
That is the strongest way to understand the project:
not as a warehouse database, but as a warehouse execution system.