MIS Test 3 Tech Reports

Cloud Computing and SaaS – What They Are

• Cloud Computing stores data in remote data centers rather than physical hardware.

• SaaS is a cloud service model where users subscribe to software hosted online.

• Cloud enables on-demand access to computing power, storage, and apps.

• SaaS uses multi-tenant architecture so one software serves multiple accounts securely.

Cloud Computing and SaaS – How Cloud Computing Works

• Cloud relies on physical data centers containing servers, hardware, and storage systems.

• Virtualization divides one physical server into multiple virtual ones to maximize capacity

• High-speed networks (WAN), load balancers, CDNs, and software-defined networking move data efficiently

• Users pay providers (hosts) for storage, communication, and infrastructure management

Cloud Computing and SaaS – How SaaS Works

• SaaS apps run on cloud infrastructure and are accessed through the internet.

• Multi-tenant design allows one application to serve many users while isolating data.

• Providers handle maintenance, updates, security, and hosting.

• Users pay subscription fees instead of installing software locally

Cloud Computing and SaaS – Value for Individuals

• Avoid installation and maintenance of hardware/software.

• Pay simple end-user fees for powerful online tools.

• Applications are accessible anytime, on any device.

• Enhances flexibility, convenience, and ease of use.

Cloud Computing and SaaS – Value for Organizations

• Reduces costs for hardware, storage, and IT staffing.

• Provides scalability (capacity adjusts with business needs).

• Enables remote work, real-time collaboration, and secure access.

• Supports faster innovation and more efficient operations.

Cloud Computing and SaaS – Key Applications

• Leading cloud platforms: Google Cloud, Microsoft Azure, AWS (~63% of global market).

• Popular SaaS examples: Slack (collaboration), Salesforce (CRM), Adobe Creative Cloud (design).

• Cloud provides on-demand compute, storage, analytics, and tools.

Cloud Computing and SaaS – Competing Technologies (Edge Computing)

• Processes data near its source (IoT devices) for real-time decision-making.

• Sends only relevant data to the cloud, reducing network load.

• Ideal for low-latency tasks and large volumes of real-time data.

• Cloud is still dominant; Edge supplements it for time-sensitive workloads.

Cloud Computing and SaaS – Technology Being Replaced

• Replaces on-premises physical infrastructure (servers, data centers, databases).

• Traditional systems require large upfront investments and fixed capacity.

• Cloud enables on-demand scaling without physical upgrades.

• 85%+ of organizations surveyed now use cloud over on-prem solutions.

Cloud Computing and SaaS – Ethical Issues

• Users must trust third-party providers with sensitive data stored remotely.

• Concerns about data ownership and providers selling data to external parties.

• Requires transparency about data collection and usage

Cloud Computing and SaaS – Security Challenges

• Cloud systems are targets for cyberattacks and data breaches.

• Example: 2014 Yahoo breach of 500M+ user accounts (names, passwords, emails).

• Strong encryption, access control, and security protocols are essential.

• Users rely on providers to secure infrastructure and data.

Internet of Things (IoT) – What It Is

• Network of everyday devices that connect to the internet and communicate with one another.

• Devices use sensors to collect data, transmit it via Wi-Fi/Bluetooth/cellular, then trigger actions.

• Actions can include alerts, recommendations, or automated responses.

• Example: Smart thermostats adjust temperature based on home activity.

Internet of Things (IoT) – Value for Individuals

• Provides convenience, automation, and real-time insights.

• Improves safety through monitoring tools (e.g., baby monitors, security devices).

• Supports healthier living through trackers and health devices.

Internet of Things (IoT) – Value for Organizations

• Enables real-time data collection for better decision-making.

• Improves operational efficiency and reduces costs.

• Supports automation in inventory tracking, equipment monitoring, and logistics.

Internet of Things (IoT) – Value for Society

• Supports smart cities and sustainable communities.

• Improves energy management through smart grids.

• Enhances public services and overall quality of life.

Internet of Things (IoT) – Everyday Applications and industry applications

Everyday Applications

• Smart home tools: baby monitors, thermostats, fridges, ovens.

• Devices monitor, alert, and adapt to user behavior.

• Enhance convenience by automating routine tasks.

Industry Applications

• Manufacturing: sensors track machines and predict maintenance.

• Transportation: GPS, cameras, sensors monitor vehicles and traffic.

• Retail: smart shelves manage real-time inventory.

• Healthcare: remote monitoring of vital signs.

• Agriculture: soil and weather sensors improve crop management.

Internet of Things (IoT) – Adjacent Tech: M2M Communication, SCADA, Edge Computing

M2M Communication

• Device-to-device communication with no human involvement.

• Used in telemedicine, fleet tracking, remote sensors.

• Efficient for specific tasks but difficult to scale broadly.

SCADA

• Industrial system for monitoring and controlling infrastructure.

• Used in electric grids, pipelines, and large-scale industrial processes.

• Reliable but legacy systems lack security and scalability

Edge Computing

• Processes data close to devices instead of relying on cloud-only systems.

• Reduces latency and boosts reliability during network disruptions.

• Used in autonomous vehicles, smart grids, industrial robotics

Internet of Things (IoT) – Interoperability Challenges, Reliability & Connectivity Problems, Device Lifespan Issues

Interoperability Challenges

• Devices from different manufacturers often fail to communicate.

• Ecosystems like Apple work smoothly internally but not cross-brand.

• Leads to fragmented, isolated systems instead of universal connectivity.

Reliability & Connectivity Problems

• IoT systems heavily depend on strong internet connections.

• Outages can disrupt essential functions (e.g., remote healthcare).

• Real-time data requires large storage and processing power.

Device Lifespan Issues

• Devices become outdated quickly and may be abandoned.

• “Zombie devices” stay connected but insecure.

• Creates long-term cybersecurity risks and maintenance burdens

Internet of Things (IoT) – Ethical Concerns (Privacy), Security Concerns, Surveillance & Autonomy Concerns, Environmental Challenges

Ethical Concerns (Privacy)

• IoT collects vast amounts of personal data (health, location, habits).

• Raises questions about ownership, consent, and potential misuse.

• Sensitive data could be exploited by insurers, employers, or third parties

Security Concerns

• Each device is a potential entry point for hacking.

• Examples: AirTag misuse, HomeKit vulnerabilities enabling device control.

• Requires strong authentication, encryption, and secure design

Surveillance & Autonomy Concerns

• IoT devices can form detailed profiles of individuals’ behavior.

• Raises risks of government overreach and corporate surveillance.

• Smart assistants and home devices blur boundaries of privacy.

Environmental Challenges

• Billions of devices become electronic waste.

• High resource and energy consumption across device lifespan.

• Contradiction between IoT’s “green” benefits and its ecological footprint.

Wireless Technologies: 5G – What It Is

• Fifth generation of wireless communication enabling higher speeds, lower latency, and massive device connectivity.

• Supports modern technologies like IoT, cloud computing, AI, machine learning (Industry 4.0).

• Evolves from 1G → 4G, each adding digital signals, mobile internet, and high-speed data.

Wireless Technologies: 5G – How It Works

• Uses low-, mid-, and high-band spectrum, with higher frequencies enabling faster data but shorter range.

• Requires dense networks of small cells/nodes on buildings, poles, and streetlights to overcome signal obstacles.

• Uses network slicing to create dedicated virtual networks tailored to specific user or industry needs.

Wireless Technologies: 5G – Key Technical Advantages

• High bandwidth → more devices supported at once.

• Ultra-low latency → rapid data transfer, essential for real-time operations.

• Lower error rates due to improved modulation and coding schemes.

Wireless Technologies: 5G – Value for Individuals &Value for Businesses

Value for Individuals

• Faster downloads and streaming.

• Smoother performance for apps, gaming, and video calls.

• Better reliability in crowded areas (stadiums, cities, events).

Value for Businesses

• Autonomous vehicles: faster communication between sensors and infrastructure.

• Healthcare: real-time surgical imaging and instant access to patient records.

• General operations: quicker data flows support automation and decision-making.

Wireless Technologies: 5G – Key Challenges

• Infrastructure gaps: expensive to deploy in rural/developing regions.

• Digital divide: limited access widens inequities as IoT and smart systems depend on 5G.

• Supply chain risks: untrusted vendors can introduce compromised equipment.

Wireless Technologies: 5G – Security Risks

• Vulnerable to malware, spoofing, and jamming attacks.

• Billions of IoT devices become entry points for cyber threats.

• Requires strong safeguards: secure networking, vetted vendors, encryption.

Wireless Technologies: 5G – Competing & Successor Technologies

• 6G (emerging): aims for lower latency, higher data rates, and improved global coverage.

• Key enablers: terahertz (THz) communication, reconfigurable intelligent surfaces (RIS), AI-optimized networks.

• Hybrid models: integration of 5G/6G with satellite networks and advanced Wi-Fi for seamless global connectivity.

Cybersecurity and Digital Trust – What They Are

• Cybersecurity = protection of an organization’s digital infrastructure and assets.

• Uses safeguards such as risk management, MFA, firewalls, encryption, and intrusion detection.

• Digital trust = confidence users have that organizations protect data ethically and reliably.

Cybersecurity and Digital Trust – How They Work

• Cybersecurity detects, prevents, and responds to digital threats.

• Digital trust forms through transparency, ethical data practices, and consistent security.

• Together, they reduce vulnerability and strengthen user confidence in digital systems.

Cybersecurity and Digital Trust – Value for Individuals, Organizations, Society

• Individuals: protects privacy, identity, and financial information.

• Organizations: avoids breaches, protects reputation, and serves as a competitive differentiator.

• Society: secures national infrastructure and supports digital commerce and innovation.

Cybersecurity and Digital Trust – Key Applications

• Used in healthcare for securing sensitive patient records and telemedicine.

• Used in education (e.g., LMS platforms) to protect student and academic data.

• Applied across industries wherever sensitive or regulated data must be safeguarded.

Cybersecurity and Digital Trust – Competing & Evolving Technologies

• Traditional tools: firewalls, antivirus, intrusion detection — effective but limited.

• Modern solutions: AI-powered security (anomaly detection, automated response).

• Zero Trust Architecture: “never trust, always verify” continuous authentication.

Cybersecurity and Digital Trust – Challenges

• Cybersecurity is a “negative deliverable”: reduces risk but can’t guarantee full protection.

• Threats evolve constantly, requiring ongoing updates and reassessments.

• Balance needed: too much security harms innovation; too little increases vulnerability.

• Some risks are hard to quantify, complicating investment decisions.

Cybersecurity and Digital Trust – Ethical & Security Concerns

• Privacy: unethical to collect data without strong protection (e.g., weak encryption).

• Transparency: users must know how their data is used and who can access it.

• Phishing threats: increasingly sophisticated, requiring user education and vigilance.

Cybersecurity and Digital Trust – Technology Being Replaced

• Replacing traditional perimeter-based security (“trust but verify”).

• New models assume threats can come from anywhere — even inside the network.

• Zero Trust + AI/ML automation → adaptive, real-time, intelligent defense systems.

Advanced Robotics & Automation – How It Works

• Integrates mechanical, electronic, and digital systems to act with limited human input.

• Uses sensors (cameras, LiDAR) + AI-based controllers for perception and movement planning.

• Operates as MIS sociotechnical systems: robots generate data fed into ERP/SCM systems to improve decisions.

• Guided by global safety standards (ISO 10218 + ISO/TS 15066).

Advanced Robotics & Automation – Value for Individuals

• Reduces repetitive and dangerous tasks.

• Enables higher-skill work: programming, monitoring, analysis.

• Represents MIS concept of informate → technology enhances human capability rather than replaces it.

Advanced Robotics & Automation – Value for Organizations

• Increases productivity, consistency, and quality.

• Provides real-time data for predictive maintenance and smarter decisions.

• Lowers operating costs and improves adaptability to demographic/environmental pressures.

Advanced Robotics & Automation – Key Applications (High-Level)

• Manufacturing: precision assembly, welding, quality control.

• Healthcare: surgical robotics, automated dispensing.

• Warehousing: material handling, order picking.

• Mining / Hazardous sectors: inspection, monitoring, safer access to dangerous areas.

Advanced Robotics & Automation – Competing Technologies

• Fixed automation: conveyor systems / hard-coded assembly lines → cost-effective for high-volume, stable tasks.

• Software automation (RPA): automates digital workflows without physical robots.

• Hybrid systems: human-robot collaboration (including AR-supported labor).

• Advanced robotics differentiates by combining physical capabilities with adaptive AI.

Advanced Robotics & Automation – Suitability Across Industries

• Suitable where precision, safety, and efficiency are essential.

• Common in healthcare, logistics, manufacturing, agriculture, mining.

• Drives major improvements in output, quality, and reduced safety incidents.

Advanced Robotics & Automation – Challenges & Problems

• High upfront cost + integration and maintenance expenses.

• Workforce displacement and skills gap (need programming/oversight skills).

• Safety standards must continually evolve with rapid technological change.

Advanced Robotics & Automation – Ethical & Security Concerns + What It Replaces

• Ethical: job displacement, wage pressure, inequality (robots replacing routine human labor).

• Security: robotics systems increase cyberattack exposure in operational environments.

• Replaces manual and semi-automated tasks; shifts work toward oversight and machine programming.

• Many jobs have 30%+ automatable tasks, reshaping the structure of work.