Postgraduate Diploma in Intelligent Waste Collection and Logistics
Online 800-hour Postgraduate Diploma in Intelligent Waste Collection and Logistics. 8 modules covering Law 7/2022 on waste and contaminated soils, Directive (EU) 2018/851 (amending the Waste Framework Directive) and ArcGIS Network Analyst. Assigned tutor and open enrolment.
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Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Compare waste collection systems and their performance.
Select sensors and connectivity technologies for containers.
Optimise collection routes using operational research tools.
Size the fleet and the service logistics.
Analyse service data to improve its efficiency.
Design pay-as-you-throw systems and citizen participation schemes.
Prepare an intelligent collection project with its procurement model.
Who it's for
- Waste collection service engineer who wants to specialise in Intelligent Waste Collection and Logistics.
- Waste logistics analyst who wants to specialise in Intelligent Waste Collection and Logistics.
- Head of street cleaning and collection service who wants to specialise in Intelligent Waste Collection and Logistics.
- Municipal waste technician who wants to specialise in Intelligent Waste Collection and Logistics.
- Procurement consultant for urban services who wants to specialise in Intelligent Waste Collection and Logistics.
- Service data specialist in the waste sector who wants to specialise in Intelligent Waste Collection and Logistics.
- Graduates in engineering or sciences seeking to join urban services companies.
What you'll work with
- Law 7/2022 on waste and contaminated soils
- Directive (EU) 2018/851 (amending the Waste Framework Directive)
- EN 840 (mobile waste containers)
- EN 12574 (fixed waste containers)
- EN 1501 (waste collection vehicles)
- Law 9/2017 on Public Sector Contracts
- ISO 39001 (road traffic safety management)
8 modules · 800 h
1.1Municipal waste fractions1.2Law 7/2022 and separate collection targets1.3Biowaste collection1.4Rear-loading, side-loading and top-loading containers1.5Door-to-door collection1.6Smart containers with identification1.7Civic amenity sites1.8Commercial collection1.9Waste generation and composition1.10Case study: service diagnosis for a municipality
2.1Ultrasonic fill-level sensors2.2Temperature and fire sensors2.3User identification by card2.4On-board weighing in lorries2.5RFID tags on bins2.6LPWAN networks for containers2.7GPS fleet tracking2.8IoT management platforms2.9Sensor maintenance2.10Laboratory: analysing fill-level sensor data
3.1Vehicle routing problem (VRP)3.2Routes with capacity and time windows3.3Dynamic routes based on fill levels3.4Heuristics and metaheuristics3.5OR-Tools and GIS tools3.6Optimal collection frequencies3.7Workload balancing3.8Urban restrictions and timetables3.9Assessment of kilometre savings3.10Practice: route optimisation with OR-Tools
4.1Types of refuse collection vehicles4.2Electric and natural gas fleets4.3Charging infrastructure4.4Transfer stations4.5Transport to treatment plants4.6Depot and workshop management4.7Predictive fleet maintenance4.8Road and occupational safety4.9Cost indicators per tonne4.10Workshop: sizing a collection fleet
5.1Integration of sensor, fleet and user data5.2Prediction of waste generation5.3Detection of anomalies and overflows5.4Service dashboards5.5Quality of the collected fraction5.6Waste traceability5.7Digital twin of the service5.8Interoperability with urban platforms5.9Protection of user data5.10Practice: fill-level prediction with machine learning
6.1Mandatory waste charge under Law 7/20226.2Pay-as-you-throw systems6.3Incentives for separation6.4Communication and campaigns6.5Mobile apps for citizens6.6Incident and alert management6.7Inspection and penalty regime6.8Equity and accessibility of the service6.9Reference European experiences6.10Case study: designing a pay-as-you-throw system
7.1Direct and indirect management models7.2Technical specifications with indicators7.3Law 9/2017 on public sector contracts7.4Penalties and service quality7.5Service cost study7.6Investment in smart technology7.7Carbon footprint of the service7.8Evaluation of alternatives7.9Contract transition7.10Workshop: indicators for a collection tender specification
8.1Diagnosis of the current service8.2Proposed collection model8.3Selection of sensors and connectivity8.4Route and frequency optimisation8.5Fleet sizing8.6Data platform and dashboard8.7Economic model and charge8.8Implementation and communication plan8.9Report and presentation8.10Final review with the tutor
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine the programme with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is ArcGIS Network Analyst, Python (OR-Tools), QGIS, Power BI, Fleet management platforms (telematics), in free, academic or evaluation versions. Case studies are based on real procedures from pilot trials of fill-level sensors in containers, collection route optimisation, service data analysis and weighing. Assessment is continuous by module, plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Compare waste collection systems and their performance.
Select sensors and connectivity technologies for containers.
Optimise collection routes using operational research tools.
Size the fleet and the service logistics.
Analyse service data to improve its efficiency.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical regulatory texts.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme consists of 800 hours in total, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
The programme uses ArcGIS Network Analyst, Python (OR-Tools), QGIS, Power BI, Fleet management platforms (telematics). Free, academic or evaluation versions are used, and the tutor indicates the open-source alternative where one exists.
A SEIUM diploma of your own upon passing the continuous assessment and the integrative project. It is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area can be credited towards the advanced programme. Please check the credit recognition policy when you enrol.
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