Module Details

Module Code: PHYS7029
Title: Smart Sensor Instrumentation
Long Title: Smart Sensor Instrumentation
NFQ Level: Intermediate
Valid From: Semester 1 - 2019/20 ( September 2019 )
Duration: 1 Semester
Credits: 5
Field of Study: 4411 - Physics
Module Delivered in: 3 programme(s)
Module Description: This modules deals with the principles, modes of operation and use of Smart Sensor instrumentation and related networking and data storage infrastructure. It provides knowledge of the communication technologies underpinning the Internet of Things (IoT) and Machine to Machine (M2M) Communication
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Identify, describe and utilize hardware and software components that constitute the traditional internet
LO2 Describe, utilize and critically analyze modern technologies that support smart sensors such as Internet of Things (IoT) and machine to machine (M2M) communications
LO3 Describe the construction, principle of operation, modes of operation and assess the application specific suitablity of a range of smart sensors.
LO4 Design, create, populate and manipulate a simple relational database and its tables for smart sensor data. Define SQL queries to select, insert, update, query and delete smart sensor data from a database.
LO5 Critically analyse the deployment of a Smart Sensor array in the home / industry / environment taking into consideration the associated data handling and analysis techniques.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 
Indicative Content
Internet Technology
Protocols:Ethernet, IPv4, IPv6, UDP, TCP, ICMP, NAT and private IP addresses. Services: DNS, DHCP, HTTP, SMPT. Operatons: Routing and Switching. Hardware Components: Routers, Switches, Wireless AP, security appliances. Networking monitoring tools: wireshark, nmap.
Smart Sensors and the Internet of Things
The evolution of Internet of Things (IoT). IoT architectures and standards in networking and communications. IoT technologies: RFID, smart sensors and sensor networks. Types of network configurations: star, ad hoc. Wireless PAN (Bluetooth- IEEE802.15 and Zigbee- IEEE 802.15.4) LAN (WiFi - IEEE 802.11) and WAN (WiMax 802.16 ) principles and protocols. Sub 1GHz standards such as LoRa/LoRaWAN. Regulatory limits on transmit power. ISM bands. Licensed bands. Security considerations.
Smart Sensors Operation
Principles of operation of smart sensors and actuators. Sensing, processing and decision making. Power budget calculations. Battery life calculations, immunity to electromagnetic interferrence. EMC Standards. Examples of smart sensors.
Smart Sensor Data Handling
Introduction to database management systems - database design and management - Structured Query Language
Smart Sensor Deployment
Application and deployment of smart sensors / actuators in modern society (building automation, transportation, vending machines, ehealth, surveillance and environmental monitoring). Machine-to-Machine communication - Network architecture, security issues and solutions.
Module Content & Assessment
Assessment Breakdown%
Coursework100.00%

Assessments

Coursework
Assessment Type Practical/Skills Evaluation % of Total Mark 25
Timing Week 4 Learning Outcomes 1
Assessment Description
Skills test based on the utilization of hardware and software components of traditional computer networks.
Assessment Type Short Answer Questions % of Total Mark 25
Timing Week 8 Learning Outcomes 2
Assessment Description
Examination based on modern technologies supporting Smart Sensing and IoT technologies
Assessment Type Reflective Journal % of Total Mark 25
Timing Every Week Learning Outcomes 3,4,5
Assessment Description
Reports on practical sessions and a mini-project based on the use of modern technologies for networking, IoT, database and smart sensing and actuation.
Assessment Type Critique % of Total Mark 25
Timing Week 13 Learning Outcomes 2,3,5
Assessment Description
Case study involving the critical analysis of a Smart Sensor system in the home / industry
No End of Module Formal Examination
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Lectures delivery of course material Every Week 1.00 1
Lab Contact Laboratory exercises supporting course material Every Week 3.00 3
Independent Learning Non Contact Independent study of course material Every Week 3.00 3
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Lectures delivery of course material Every Week 1.00 1
Lab Contact Laboratory exercises supporting course material Every Week 2.00 2
Directed Learning Non Contact Assignments and projects / case studies Every Week 1.00 1
Independent Learning Non Contact Independent study of course material Every Week 3.00 3
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • William Stallings. (2014), Data and Computer Communications, Prentice Hall, [ISBN: 9780133506488].
  • Shuang-Hua Yang. (2016), Wireless Sensor Networks, Springer, [ISBN: 9781447169321].
This module does not have any article/paper resources
Other Resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_SESST_8 Bachelor of Science (Honours) in Environmental Science and Sustainable Technology 3 Elective
CR_SINEN_8 Bachelor of Science (Honours) in Instrument Engineering 6 Elective
CR_SPHYS_7 Bachelor of Science in Applied Physics and Instrumentation 6 Elective