FLEET MANAGEMENT USING GSM & GEOSPATIAL TECHNOLOGIES CASE: STUDY DOUBLE M BUS SERVICES.

Transcription

1 FLEET MANAGEMENT USING GSM & GEOSPATIAL TECHNOLOGIES CASE: STUDY DOUBLE M BUS SERVICES. GIDEON MUTUA MUSYOKA F19/2465/2009 Supervisor: DR. ING D.N SIRIBA mutgideon@gmail.com

2 OUTLINE OF PRESENTATION Introduction Background to the study 2. Problem statement 3. Objectives of the study 1. Methodology Area of study 2. Data and their sources 3. Overview of methodology 1. Results and Analysis Conclusions and Recommendations Q/A Session

3 INTRODUCTION Background of the Study Fleet management is the management of a company's transportation fleet. Fleet management includes commercial motor vehicles such as matatus / mathrees, cars, buses and trucks. Fleet management is the most important function in any bus based transport company. It involves scheduling and planning routes and ensuring that the buses run as per the schedule. Fleet management essentially involves ensuring timely arrival and dispatch of buses. To go a step further fleet management systems have proven to be effective in determining the precise location of a vehicle, dispatch, on-board information and vehicle recovery in case of theft.

4 PROBLEM STATEMENT Double M bus services has 256 buses and these buses make about 5000 trips daily, and these trips pass through repeatedly about 400 bus stops in the Nairobi city. It is very difficult to manage a big fleet in big cities like Nairobi, where these buses perform repetitive trips. Failure of proper management in timely operations has resulted in the collapse of big bus based transport companies This project attempts to show how we can take advantage of Global System for Mobile communications (GSM) and Geospatial technologies Global Navigation Satellite Systems (GNSS) and Geographic Information System (GIS), to better manage a fleet

5 OBJECTIVES General objective The objective of this project is to demonstrate a Fleet Management System using GSM and Geospatial Technologies. Specific objectives O To digitize the road map of Nairobi city O To create bus route map within Nairobi city O To develop a geo-database for storing vehicle trip data generated by in-vehicle hardware O To analyze vehicle trip information generated by in-vehicle hardware O To demonstrate an animation showing vehicle movement over time

6 METHODOLOGY

7 AREA OF STUDY The study was carried out in Nairobi County, one of the 47 Counties of Kenya Nairobi has a total area of approximately 696 square Kilometers, at lies at zone 36 between longitudes E and E and latitude 1 09 S and 1 27 S. Nairobi s population is about 3,375,000 (2013). Average elevation of Nairobi is about 1660M above MSL.

8 DATA & SOURCES Data Characteristics Source Latitude Vehicle trip information Longitude Speed Time Date Installed GSM/ GPS/ GPRS tracking hardware in vehicle Nairobi road network shapefile Arc 1960 datum ILRI Bus routes dataset CSV file Digital matatus website (

9 Hardware Material Source Purpose Specifications Laptop Personal Data editing, manipulation, Dell Inspiron analysis, and report writing. 2.3 GHz processor 2 GB RAM 500 GB Hard disk GPS Module:Sirf3 chip Band 850/900/1800/1900Mhz SMS tracking on cellphone Fuel sensors support Start/ Stop vehicle engine remotely GNSS blind spot alerts SOS button, Geo fence, movement, over speed, low battery and GPS/GSM/ GPRS Tracker (TK106) Satrack Kenya Bus tracking power off alerts Mobile phone Personal Voice Monitoring Receiving vehicle tracking Samsung GalaxyS4 information as SMS and 16GB internal storage sending commands to the 2GB RAM tracker SMS threads display Flash disk Personal Data transfer 8GB storage Printer Satrack Kenya Production of hardcopy HP Deskjet D2600 series A4 documents 4 SIM cards Safaricom Inserting in trackers (15.00x12.00x0.76) Safaricom Micro-SIM

10 Software Software Source Purpose ArcGIS(ArcMap version 10.1) Global Mapper version 11.0 Oakar services Oakar services Analysis of data Converting projections Google earth pro Personal copy Creating kml files Microsoft Excel 2013 Microsoft Presenting and editing vehicle report data Microsoft Word 2013 Microsoft Report writing Adobe Photoshop Satrack Kenya Graphic design

11 OVERVIEW OF METHODOLOGY DATA IDENTIFICATION DATA COLLECTION SPATIAL DATA NON SPATIAL DATA DIGITAL ATTRIBUTE TABLES DATA TRANSFORMATION DATABASE DEVELOPMENT DATA PROCESSING RESULS ANALYSIS

12 Data Collection

13 Data collection cont.. O One TK106 GSM/ GPS/ GPRS tracker was hardwired on KBN432S engine with a known SIM card number. On 13th February 2014 at 8:21:00 AM, the tracking process was started and the tracker set to auto-send tracking information at intervals of 30 seconds to a cell phone. O The other three vehicles were not installed a tracker instead the mini version of TK106 which is portable and with a built in battery was used. Three different people who were helping in carrying out the exercise entered buses, KBJ126P, KBK023Q and KBX670T at different locations around the same time. O Tracking for vehicle KBJ126P was started at 7:56:00 AM and ended at 8:55:00 AM with tracking intervals set at 60 seconds. O The third bus KBK023Q which was from Mombasa road was tracked from 9:23:10 AM and tracking stopped at 10:40:10 AM. The last bus KBX670T was tracked from 9:34:20 AM and tracking stopped at 10:42:20 AM with intervals set at 60 seconds as well.

14 RESULTS AND DISCUSSIONS

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20 Part of Geodatabase for Bus trip information

21 A schematic diagram showing animation of vehicle movement

22 Interpretation of Results Vehicle trip interpretation O Vehicle KBJ126P was tracked from Wangige through Gitaru road, then collected passengers around Kikuyu area, travelled through waiyaki way then diverted to Naivasha road and entered Nairobi CBD through Ngong road, maybe the driver was avoiding traffic jam which is normally heavy along Waiyaki way in the e morning hours. O The second bus, KBK023Q, was tracked from Mombasa road, then it diverted to South C area perhaps to pick some passengers. Later, the bus rerouted to Mombasa road all the way through Haile Salassie Avenue, then racecourse road and finally bus station. O The third bus, KBN432S, was tracked from Kangemi bus terminus, near Kangemi market through waiyaki way, then it stopped at Westlands stage to drop passengers and ferried the rest to Nairobi CBD through Uhuru highway then University way. This bus however changed route to Eastlands. It used landies road, then jogoo road and diverted at jogoo road, then mumias south road near bururu area, the Kariobangi south which was its destination. O The last bus, KBX670T, was tracked from Kawangware, (46 mwisho bus stage) through Gitanga road, then Argwings Kodhek road, valley road, Kenyatta avenue, Dedan Kimathi street and finally Bus station.

23 CONCLUSIONS O The study found out that double m bus services just like most bus based transport companies in Kenya do not use modern technologies to better manage their fleet, instead they carry out manual tracking by posting inspectors at some important points. O Fleet management solutions provide significance value to bus based transport companies. By implementing a fleet solution that combines GSM and Geospatial technologies, organizations can maximize benefits and minimize costs. O The objective of this study was successfully achieved.

24 Recommendations The following recommendations were suggested for this study: O Before starting data collection, someone should ensure enough airtime is in the sim cards because lack of enough airtime means they will not be able to receive tracking messages. O The digital government should make it a policy for every PSV Company or Sacco to have a digital management system for their fleet.

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