-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathdomain.html
More file actions
404 lines (394 loc) · 20 KB
/
Copy pathdomain.html
File metadata and controls
404 lines (394 loc) · 20 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>TruGanic | Domain</title>
<meta
name="description"
content="Domain details of the TruGanic research project including literature survey, research gap, objectives, methodology, and technologies."
/>
<link rel="preconnect" href="https://fonts.googleapis.com" />
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin />
<link
href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&family=Playfair+Display:wght@600;700&display=swap"
rel="stylesheet"
/>
<link rel="stylesheet" href="./css/style.css" />
</head>
<body>
<header class="site-header">
<nav class="navbar container" aria-label="Main navigation">
<a href="./index.html" class="brand">TruGanic</a>
<button
class="nav-toggle"
type="button"
aria-expanded="false"
aria-controls="primary-menu"
>
Menu
</button>
<ul class="nav-links" id="primary-menu">
<li><a href="./index.html">Home</a></li>
<li><a href="./domain.html">Domain</a></li>
<li><a href="./milestones.html">Milestones</a></li>
<li><a href="./documents.html">Documents</a></li>
<li><a href="./presentations.html">Presentations</a></li>
<li><a href="./about.html">About Us</a></li>
<li><a href="./contact.html">Contact Us</a></li>
</ul>
</nav>
</header>
<main>
<section class="domain-hero section-spacing">
<div class="container domain-hero-layout">
<div class="domain-hero-content">
<p class="eyebrow">Domain</p>
<h1 class="domain-title">Project Domain Overview</h1>
<p class="domain-intro">
This page presents a complete domain-level view of the TruGanic
research, covering how existing knowledge shaped the solution and
why the proposed architecture is needed in real organic food
supply chains from farm evidence to the buyer. It briefly ties
source data, logistics continuity, readable provenance, and
security so you can see how those pieces belong in one system
before the sections below expand each part. It explains the
literature survey outcomes, the
detailed <a href="#research-gap">research gap</a>, the core
<a href="#research-problem">research problem</a>, the
<a href="#research-objectives">objective</a> structure, the
implementation <a href="#methodology">methodology</a>, and the
<a href="#technologies-used">technology stack</a> used to deliver
a secure and production-ready system. You can also start from the
<a href="#literature-survey">literature survey</a> section.
</p>
<a href="#literature-survey" class="btn-primary">Explore Domain</a>
</div>
<div class="hero-visual" aria-label="Domain hero image">
<div class="blob">
<div class="blob-bottom-clip" aria-hidden="true">
<img
class="hero-person hero-person-base"
src="./assets/images/DomainHero.png"
alt=""
/>
</div>
<img
class="hero-person hero-person-pop"
src="./assets/images/DomainHero.png"
alt="Project team collaborating in a planning meeting"
/>
</div>
</div>
</div>
</section>
<section class="section-spacing domain-sections">
<div class="container domain-flow">
<article class="domain-row" id="literature-survey">
<div class="domain-text">
<h2>Literature Survey</h2>
<p>
Existing research confirms that blockchain can improve
traceability in agri-food systems by offering immutability,
shared visibility, and stronger provenance verification across
farmers, certifiers, logistics agents, and retailers. However,
review studies also emphasize that blockchain alone does not
guarantee trustworthy data input, especially at the farming
stage where manual submissions and sensor streams may contain
anomalies or inconsistencies. This has led recent work to
integrate machine learning based validation as an upstream
screening mechanism, particularly using anomaly detection
techniques to identify suspicious soil behavior before final
traceability claims are accepted.
</p>
<p>
The literature also highlights major logistics constraints in
real deployments. Field and transport environments often face
unstable connectivity, making continuous online syncing
unrealistic. Local-first and offline-first approaches are
therefore recommended to preserve data capture continuity and
later synchronization with integrity checks. At the consumer
layer, studies show that raw ledger records are too technical
for public trust decisions. AR-based visualization has emerged
as a practical method to convert technical provenance into
understandable quality indicators. Security-oriented studies
further support Zero Trust adoption in blockchain-backed
platforms so no system component is blindly trusted after
compromise, reinforcing trustworthy organic claims end-to-end.
</p>
</div>
</article>
<article class="domain-row" id="research-gap">
<div class="domain-text">
<h2>Research Gap</h2>
<p>
The literature shows good progress in individual areas, but
there is still no widely adopted framework that connects all
critical layers in one practical and secure organic traceability
flow. Current systems often solve one part well while leaving
major operational and trust gaps in other stages.
</p>
<p>
A key gap appears at the source-data layer. Even when
blockchain is used, most implementations still trust submitted
values without enough intelligent screening before permanent
recording. This creates a quality-risk gap where immutable
records can still preserve poor or suspicious data. In organic
supply chains, this problem is critical because certification
decisions depend on early-stage farm evidence and handling
conditions that must be credible, not only tamper-resistant.
</p>
<p>
Another major gap is operational resilience across transport
environments. Many existing solutions assume stable
connectivity, while real logistics routes often include rural
and low-signal regions. Without robust offline-first behavior,
systems risk incomplete event histories, delayed logging, and
inconsistent cold-chain monitoring records. This weakens the
end-to-end continuity expected in trustworthy traceability.
</p>
<p>
A further gap exists in consumer communication and trust
interpretation. Although provenance data may be available on
blockchain, most platforms provide technical logs that are
difficult for non-technical users to understand. There is
limited implementation of user-friendly insight layers that
translate raw records into clear quality indicators, confidence
levels, and actionable trust signals at the point of purchase.
</p>
<p>
Security integration is also underdeveloped. Current work rarely
embeds a formal Zero Trust security architecture across all
modules of blockchain-backed traceability. In practice, this
means systems may still over-trust internal components, devices,
or services after compromise. The identified gap is therefore
not only functional integration, but also security-by-design
integration that continuously verifies identities, data states,
and transaction legitimacy before trust is granted.
</p>
<ul class="domain-list">
<li>
<strong>Data credibility gap:</strong> Blockchain keeps records
immutable, but most systems still depend on unverified input
data from farm-level sources.
</li>
<li>
<strong>Logistics continuity gap:</strong> Many solutions assume
stable internet and do not provide robust offline-first
capture with integrity validation during transport.
</li>
<li>
<strong>Consumer interpretability gap:</strong> Provenance logs
are often too technical, and only a few systems convert them
into simple trust indicators for end users.
</li>
<li>
<strong>Integration gap:</strong> Anomaly detection, offline
synchronization, and AR communication are mostly implemented
separately instead of in one end-to-end architecture.
</li>
<li>
<strong>Security architecture gap:</strong> Explicit Zero Trust
integration in blockchain-backed traceability remains limited,
especially for handling compromised components without blindly
trusting organic claims.
</li>
</ul>
</div>
</article>
<article class="domain-row" id="research-problem">
<div class="domain-text">
<h2>Research Problem</h2>
<p>
Traditional systems struggle to assure trustworthy data at
source, maintain records during connectivity disruptions, and
present traceability evidence in a simple form users can trust.
</p>
<p>
The core research problem is the absence of a practical
end-to-end mechanism that can maintain trust integrity from farm
to consumer in real-world organic food supply chains.
Conventional solutions typically focus on record storage but do
not adequately validate data quality before entry, do not handle
transport-stage network instability reliably, and do not present
provenance results in a user-friendly decision format.
</p>
<p>
At the farming stage, the problem is how to identify suspicious
soil behavior and possible data mismatches before records become
trusted evidence. At the logistics stage, the problem is how to
ensure uninterrupted event capture and verifiable integrity when
mobile connectivity is intermittent. At the consumer stage, the
problem is how to transform technical blockchain outputs into
understandable quality and trust indicators that can support
purchase decisions.
</p>
<p>
In addition, there is a security problem across the entire flow:
systems often assume internal components are trustworthy after
initial authentication. For blockchain-backed organic
traceability, this is insufficient. The research therefore
addresses how to integrate Zero Trust principles so trust is
continuously verified, and organic claims are not blindly
accepted when any subsystem may be compromised.
</p>
</div>
</article>
<article class="domain-row" id="research-objectives">
<div class="domain-text">
<h2>Research Objectives</h2>
<p>
The objective of this research is to design and validate a
practical, production-ready framework that improves trust,
continuity, and interpretability in organic food traceability.
The system is built to operate under real field constraints and
security risks while maintaining reliable evidence from source
to consumer.
</p>
<ul class="domain-list">
<li>
Develop a farm-stage anomaly detection mechanism to identify
suspicious soil patterns before blockchain recording.
</li>
<li>
Implement an offline-first logistics workflow that preserves
transport records during network loss and synchronizes them
with integrity verification.
</li>
<li>
Build an Insight Engine that converts technical provenance
data into clear, consumer-friendly trust indicators.
</li>
<li>
Provide an AR-based visualization layer for intuitive access
to batch-level traceability details at the point of purchase.
</li>
<li>
Integrate Zero Trust security controls into the
blockchain-backed architecture to avoid blind trust in
compromised components.
</li>
<li>
Evaluate the framework for anomaly detection quality,
logistics continuity, integrity assurance, and user
interpretability.
</li>
</ul>
</div>
</article>
<article class="domain-row" id="methodology">
<div class="domain-text">
<h2>Methodology</h2>
<p>
The methodology follows an end-to-end pipeline with
research-driven modules from the paper and security controls
from the TruGanic platform implementation. The flow is organized
into farm intelligence, logistics resilience, consumer insight,
and Zero Trust enforcement across all API interactions.
</p>
<p>
<strong>1) Farm-stage anomaly intelligence:</strong> Soil
readings (N, P, K, EC) from farmer input and sensor streams are
ingested at fixed intervals, transformed with delta-based
features, and screened using an Isolation Forest model. Instead
of immediate punitive action, flagged anomalies are
cross-referenced with contextual logs before recording
traceability-relevant outputs on chain.
</p>
<p>
<strong>2) Offline-first logistics continuity:</strong>
Transport events and environmental readings are captured in a
mobile workflow that supports local caching during connectivity
loss. Records are queued and synchronized when network access is
restored. A Merkle-root based integrity step is used to verify
that offline-captured trip data has not been altered before
final ledger anchoring.
</p>
<p>
<strong>3) Consumer insight and AR communication:</strong>
Blockchain batch records are processed by an insight service to
generate understandable indicators such as freshness,
cold-chain compliance, organic quality, and overall trust score.
These outputs are delivered to a QR-triggered AR interface so
users can interpret provenance evidence in a practical visual
form rather than raw technical logs.
</p>
<p>
<strong>4) Zero Trust security architecture (repo-backed):</strong>
At the platform edge, TruGanic enforces a gateway-based Zero
Trust model using DID and Verifiable Credentials for
client/agent authentication and authorization. Each request is
verified with signature, nonce, timestamp, and VC permission
checks before reaching downstream services. Inside domain
services, JWT is used for user-level session context, creating a
layered model where Zero Trust controls client-to-platform
access and JWT controls user-to-resource access.
</p>
<p>
This combined methodology ensures that traceability is not only
immutable but also context-validated, connectivity-resilient,
user-interpretable, and continuously verified under compromised
component assumptions.
</p>
</div>
</article>
<article class="domain-row" id="technologies-used">
<div class="domain-text">
<h2>Technologies Used</h2>
<p>
The solution combines blockchain infrastructure, AI-driven data
validation, offline-capable mobile components, and layered
security services to support a production-ready traceability
pipeline.
</p>
<ul class="domain-list">
<li>
<strong>Blockchain and storage:</strong> Hyperledger Fabric
(permissioned ledger), CouchDB (state queries), and IPFS
(off-chain content addressing).
</li>
<li>
<strong>AI and anomaly analytics:</strong> Isolation Forest
model with delta-based feature engineering for soil anomaly
screening (NPK/EC patterns).
</li>
<li>
<strong>Backend services:</strong> FastAPI-based insight and
processing services, plus Node.js/TypeScript microservices in
the TruGanic platform core.
</li>
<li>
<strong>Offline transport layer:</strong> SQLite-backed local
caching and delayed synchronization workflow with integrity
verification.
</li>
<li>
<strong>Zero Trust security stack:</strong> DID resolution,
Verifiable Credential issuance/verification, policy-based
authorization, nonce/timestamp replay protection, and audit
logging at the gateway-security layer.
</li>
<li>
<strong>User and visualization layer:</strong> Unity +
Vuforia for AR-based consumer presentation of trust and
provenance indicators.
</li>
<li>
<strong>Supporting infrastructure:</strong> PostgreSQL and
Redis for service data, caching, and operational support in
platform services.
</li>
</ul>
</div>
</article>
</div>
</section>
</main>
<footer class="site-footer">
<div class="container">
<p>© 2026 TruGanic. All rights reserved.</p>
</div>
</footer>
<script src="./js/main.js"></script>
</body>
</html>