1. Citizens' Appeal:
Ensuring Expeditious And Timely Justice To All
Indian Institute of Technology Ropar
Team : प्रतिबिम्ि
Annanya Sarthak
Jaspreet Kaur
Kshitij Gupta
Manjeet Yadav
Tanvi Srivastava

2. 0
50,000
100,000
150,000
200,000
250,000
300,000
MP HC Gujrat HC Assam HC Delhi HC
Supreme Court
High Courts
Other Trial Courts
Pending Cases in Various High Courts
Pending Cases in Various Courts
• 67,964 cases pending in Supreme
Court [as on 31st March 2013].
• Approximately 43 lac cases pending
in high courts.
• More than 3 Cr cases pending in
other trial courts throughout India.
Current Scenario
15-18 million fresh fillings every year.
Pending Cases Expected to rise to 15 Cr by 2040.
Developed Nations : 50 judges per million
population
Most Developing Nations : 35-40 judges per
million population.
India : 13 judges per million population.
Government’s Prime Strategy: Doubling the number
of judges (15000 new posts) in the next 5 years.

3. Automated
Screening
System
E-Conference
Courts
Improved
Existing Model
Automated
Screening
System
• Self learning, intelligent system aimed at eliminating the preliminary hearing of a
case using an automated procedure that analyses the information complementing
the case.
E-Conference
Courts
• Innovative system striving towards bringing courts to the masses, replacing the need
of additional courtroom infrastructure with the help of Internet.
Improved
Existing Model
• Efficient improvisation of the existing model with use of optimum scheduling
algorithms.
OVERVIEW OF SOLUTION PROPOSED

4. AUTOMATED SCREENING
SYSTEM
Online Case-Filing
Filtering According
to Severity
Threshold
Filtering Based on
Analysis of
Previous Cases
Passing Suspected
Frivolous Cases to
Judge for Second
Opinion.
Scheduling Non-
Frivolous Cases.
Feed Decision
Back Into System
(Self Learning )
• Type of case (as classified according to its severity).
• Area of Jurisdiction.
• Personal Information of Plaintiff and Accused.
• Evidences and witness’ testimonies (if any).
Online Case-Filing
• Recommend the case to be tried if it exceeds the severity
threshold (decided by panel of judges/lawyers and analysts).
Filtering According
to Severity
Threshold
• Search similar cases in the database.
• On basis of analysis, parameters for which are decided by
panel of lawyers/judges, decide the category under which
the case falls.
Filtering Based on
Analysis of Previous
Cases
• If the case is found to be non – frivolous, recommend it to be
tried directly.
• If found to be frivolous, pass it on to a judge for a second
opinion.
Segregation
• Decision taken is fed back to the system to hone its self
learning capability.
• Initially, run system parallel with judiciary, testing its decision
making ability and improving it by feeding it actual data.
Machine Self
Learning

5. Team Structure
IT Team
Cyber
Security
Team
Database
Management Team
Panel of
Lawyers/Judges &
Data Analysts
Database
Management Team
•Feed All
Existing
Case-Files
Into
Database.
Panel of
Lawyers/Judges &
Data Analysts
•Setup
Threshold
and other
Parameters
Required by
System.
Internet Technology
(IT) Team
•Setup
Online
Portal for
filing cases.
Cyber Security Team
•Ensure
network
security to
prevent
misusage of
data.
Cost to Government
Server (Initial Investment) 7,00,000
Domain (pa) 8,500
Median Salary of IT Engineer (pa) 3,65,000
Median Salary of Lawyer (pa) 10,00,000
Median Salary of Judge (pa) 6,00,000
Median Salary of Data Analyst (pa) 3,07,000

6. Facts
• Number of judges in trials courts = 18000 (J1)
• Number of judges in high and
supreme courts (approx.) = 1000 (J2)
• Total number of judges (J1+J2) = 19000
• Number of cases decided by an average
judge in trial courts (per year) = 1350 (N1)
• Number of cases decided by an average
judge in high and supreme courts = 2374 (N2)
• Number of pending cases till
March 2013 = 3 Cr (i)
• Expected number of pending cases
by 2040 = 15 Cr (ii)
• Average time taken in one
preliminary hearing = 1/4 hr.
Analysis
• Total number of cases solved in trial
courts in 1 year (J1*N1) = 2,43,00,000
• Total number of cases solved in
high and supreme courts (J2*N2) = 23,74,000
• Total number of cases solved = 2,66,74,000
• From (i) & (ii), number of pending cases is increasing
every year, hence number of cases registered in 1 year
is greater than number of cases solved in that year.
• So, approximate number of registered
cases in one year = 2,66,74,000
• Number of hours spent on preliminary
hearings in 1 year (2,66,74,000*1/4) = 66,68,500
• Therefore, number of hours saved by
Automated Screening System, per judge,
in 1 year (66,68,500/19000) = 351
Quantification – Automated Screening System

7. TV Screen in Judge’s cabin
Police Station 1
Party 1: Plaintiff,
Lawyer, Witnesses
Police Station 2
Party 2: Accused,
Lawyer, Witnesses
The E-Conference Court [ECC] Model
Set-up of Video Conferencing facilities in
Indian Courts and Police Stations.
Judges provided with TV monitors in their
cabins.
Plaintiff and Accused schedule date for
hearing from available slots via online means.
Both the parties , with their lawyers and
witnesses, go to the nearest police station for
hearing.
The police station connects both the parties to
the Judge in-charge and the hearing proceeds
via Three-Way Conferencing.

8. Implementation
Strategy
Set up Video Conferencing
systems in Courts and
Police Stations.
Develop online Video
Conferencing interface.
This is to be outsourced.
Appoint new Judges and
recruit technicians.
Awareness Campaigns
about the functioning of
ECCs among the masses.
Utilize Government
funding to meet
expenditures.
Installation Cost = Rs. 265 Cr
(Refer next Slide)
Operational Cost = Rs. 1050 Cr
(Refer next Slide)
Rs. 1315 Cr (starting
capital)
Implementation
Cost of ECC
Advantages of E-Conference Courts
• Additional cases handled along with the ones being tried in physical courts.
• Efficiency of the courts double by this model. As a result 5,33,48,000 cases
can be solved per annum compared to 2,66,74,000 pa.
• Easy and quick deployment.
• Minimal installation and operational cost, leading to high feasibility.
• All the police stations get connected, enhancing National Security.
Challenges
• Increasing No. of Judges
• Making the system user
friendly for technologically
handicapped people.
Mitigation
• Opening more vacancies &
glorifying the profession.
• Workshops & seminars to be
conducted.

9. Type of Cost Trivial Solution E-conference courts [ECC] Solution
Development Cost Development Cost
Installation Cost 1000 more courts required
to double the efficiency of
Indian Judiciary to clear
backlog cases.
Rs. 50 Cr investment per
court.
Rs. 50,000 Cr 19000 systems need to be installed to double the
efficiency of Indian Courts(1 system /judge).
Each system costs Rs.1 lac (approx.).
Rs.190 Cr
15000 systems need to installed in various Police
stations.
Each system costs Rs.50,000 (extension of
CCTNS).
Rs.75 Cr
Operational Cost 100 employees per court
needed for 1000 courts.
Average Package to
employees is 5lpa (approx.)
Rs. 50,000 Cr
pa
19,000 technicians with average package of 3lpa
recruited to manage Court’s systems.
570 Cr pa
15,000 technicians with average package of 3lpa
recruited to mange systems in Police Stations.
450 Cr pa
ECC saves one time cost
Rs. 49,735 Cr
ECC saves Rs.48,950 Cr
per annum
There could be various approaches to solve the big pile of pending cases.
One trivial approach is to increase the number of courts.
The other effective approach is our model of E-CONFERENCE COURTS.
The economic analysis for doubling the efficiency of Indian Judiciary system favors the implementation
of our model, the evidence follows.
Viability Assessment of E-Conference Courts

10. • Implementation of a Dual Shift Scheme such that a court functions for two consecutive shifts:
8 A.M to 1 P.M and 2 P.M to 7 P.M.
• Scheduling judicial staff’s vacations in such a manner that a court remains operational throughout the year (without
compromising the number of holidays received by judicial staff).
• Levy an appropriate fine for being absent on a hearing without prior notice.
Take Judicial staff’s preferences regarding shifts and
holidays
Schedule their shifts, trying to meet most preferences.
Schedule their vacations, giving priority to those judges
and supporting staff whose shift preference had not been
met
Improved Existing Model
Impact Assessment
•Efficiency of the current system is doubled with Dual
Shift System.
•Lesser number of people missing their hearings on
account of more flexible court schedule and to avoid
fine.
•Fifty holidays every year can be alternated among
judges keeping the courts functional during entire
period.
•In a day, 73,080 (2,66,74,000/365) cases are solved.
•Additional 50 working days imply 36,53,972
(73,080*50) more cases are solved in a year.

11. Challenges
Inertia among
judicial staff in
accepting the
Improved Existing
Model
Sensitive
information may be
accessed by parties
with mal-intent.
In Automated
Screening System,
Parameters on
which case is to
judged are
sensitive.
Mitigation
Providing Extra
perks and sensitizing
them about current
scenario and
proposed
improvements
Monitor cyber
security regularly.
Careful analysis of
parameters by a
panel of experts.

12. References
Judge-Population Ratio | Times of India
Cases solved per Judge| Research by Manthan
Total Pending Cases | Deccan Chronicles
Median Salaries | payscale.com
Court Holidays | Supreme Court Website
Pending Cases SC | Supreme Court Website
Pending Cases MP HC| MP High Court Website
Pending Cases Assam| Guwahati HC Website
Pending Cases Delhi HC| Delhi HC Website
Pending Cases HCs | IBN Live
Pending Cases Gujarat HC | IBN Live
Expected Pending Cases | Times of India